Mercurial > repos > bgruening > sklearn_numeric_clustering
annotate numeric_clustering.xml @ 22:f1ef5f9320d7 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c64ccc5850c8e061a95fb64e07ed388384e82393
| author | bgruening |
|---|---|
| date | Thu, 11 Oct 2018 03:33:22 -0400 |
| parents | 1d6d938e7ee2 |
| children | 9d234733ccfd |
| rev | line source |
|---|---|
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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1 <tool id="sklearn_numeric_clustering" name="Numeric Clustering" version="@VERSION@"> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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2 <description></description> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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3 <macros> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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4 <import>main_macros.xml</import> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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5 </macros> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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6 <expand macro="python_requirements"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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7 <expand macro="macro_stdio"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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8 <version_command>echo "@VERSION@"</version_command> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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9 <command><![CDATA[ |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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10 python "$cluster_script" '$inputs' |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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11 ]]> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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12 </command> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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13 <configfiles> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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14 <inputs name="inputs"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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15 <configfile name="cluster_script"> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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16 <![CDATA[ |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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17 import sys |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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18 import json |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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19 import sklearn.cluster |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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20 import pandas |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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21 from sklearn import metrics |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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22 from scipy.io import mmread |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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23 |
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21
1d6d938e7ee2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2a058459e6daf0486871f93845f00fdb4a4eaca1
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24 exec(open("$__tool_directory__/utils.py").read(), globals()) |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
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25 |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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26 input_json_path = sys.argv[1] |
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f02f05990cc9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48
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27 with open(input_json_path, "r") as param_handler: |
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f02f05990cc9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48
bgruening
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28 params = json.load(param_handler) |
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f02f05990cc9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48
bgruening
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29 |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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30 |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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31 selected_algorithm = params["input_types"]["algorithm_options"]["selected_algorithm"] |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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32 |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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33 my_class = getattr(sklearn.cluster, selected_algorithm) |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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34 cluster_object = my_class() |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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35 options = params["input_types"]["algorithm_options"]["options"] |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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36 |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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37 cluster_object.set_params(**options) |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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38 |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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39 #if $input_types.selected_input_type == "sparse": |
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f02f05990cc9
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48
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40 data_matrix = mmread("$infile") |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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41 #else: |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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42 data = pandas.read_csv("$infile", sep='\t', header=0, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False ) |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
parents:
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43 header = 'infer' if params["input_types"]["header"] else None |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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44 column_option = params["input_types"]["column_selector_options"]["selected_column_selector_option"] |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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45 if column_option in ["by_index_number", "all_but_by_index_number", "by_header_name", "all_but_by_header_name"]: |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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46 c = params["input_types"]["column_selector_options"]["col"] |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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47 else: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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48 c = None |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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49 data_matrix = read_columns( |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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50 "$infile", |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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51 c = c, |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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52 c_option = column_option, |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
parents:
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53 sep='\t', |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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54 header=header, |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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55 parse_dates=True, |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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56 encoding=None, |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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57 tupleize_cols=False |
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40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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58 ) |
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0
c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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59 #end if |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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60 |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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61 prediction = cluster_object.fit_predict( data_matrix ) |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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62 |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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63 if len(np.unique(prediction)) > 1: |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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64 silhouette_score = metrics.silhouette_score(data_matrix,prediction,metric='euclidean') |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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65 else: |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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66 silhouette_score = -1 |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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67 sys.stdout.write('silhouette score:' + '\t' + str(silhouette_score) + '\n') |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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68 |
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14
6bbf5cb20652
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 7c2fd140e89605fe689c39e21d70a400545e38cf
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69 prediction_df = pandas.DataFrame(prediction, columns=["predicted"]) |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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70 |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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71 #if $input_types.selected_input_type == "sparse": |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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72 res = prediction_df |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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73 #else: |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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74 res = pandas.concat([data, prediction_df], axis=1) |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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75 #end if |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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76 |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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77 res.to_csv(path_or_buf = "$outfile", sep="\t", index=False, header=False) |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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78 ]]> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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79 </configfile> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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80 </configfiles> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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81 <inputs> |
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82 <conditional name="input_types"> |
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83 <param name="selected_input_type" type="select" label="Select the format of input data"> |
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84 <option value="tabular" selected="true">Tabular Format (tabular, txt)</option> |
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85 <option value="sparse">Sparse Vector Representation (mtx)</option> |
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86 </param> |
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87 <when value="sparse"> |
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88 <param name="infile" type="data" format="txt" label="Sparse vector (scipy.sparse.csr_matrix) file:" help="The following clustering algorithms support sparse matrix operations: ''Birch'', ''DBSCAN'', ''KMeans'', ''Mini BatchK Means'', and ''Spectral Clustering''. If your data is in tabular format, please use other clustering algorithms."/> |
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89 <expand macro="clustering_algorithms_options"/> |
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90 </when> |
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91 <when value="tabular"> |
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92 <param name="infile" type="data" format="tabular" label="Data file with numeric values"/> |
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13
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93 <param name="header" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="True" label="Does the dataset contain header:" /> |
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94 <conditional name="column_selector_options"> |
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95 <expand macro="samples_column_selector_options" col_name="col" multiple="true" infile="infile"/> |
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96 </conditional> |
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0
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97 <!--expand macro="clustering_algorithms_options"--> |
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98 <conditional name="algorithm_options"> |
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99 <param name="selected_algorithm" type="select" label="Clustering Algorithm"> |
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100 <option value="AgglomerativeClustering">Hierarchical Agglomerative Clustering</option> |
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101 <option value="AffinityPropagation">Affinity Propagation</option> |
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102 <option value="SpectralClustering">Spectral Clustering</option> |
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103 <option value="MiniBatchKMeans">Mini Batch KMeans</option> |
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104 <option value="MeanShift">MeanShift</option> |
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105 <option value="KMeans">KMeans</option> |
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106 <option value="DBSCAN">DBSCAN</option> |
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107 <option value="Birch">Birch</option> |
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108 </param> |
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109 <when value="KMeans"> |
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110 <expand macro="kmeans_advanced_options"/> |
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111 </when> |
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112 <when value="DBSCAN"> |
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113 <expand macro="dbscan_advanced_options"/> |
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114 </when> |
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115 <when value="Birch"> |
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116 <expand macro="birch_advanced_options"/> |
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117 </when> |
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118 <when value="SpectralClustering"> |
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119 <expand macro="spectral_clustering_advanced_options"/> |
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120 </when> |
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121 <when value="MiniBatchKMeans"> |
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122 <expand macro="minibatch_kmeans_advanced_options"/> |
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123 </when> |
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124 <when value="AffinityPropagation"> |
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125 <section name="options" title="Advanced Options" expanded="False"> |
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126 <param argument="damping" type="float" optional="true" value="0.5" label="Damping factor" help="Damping factor between 0.5 and 1."/> |
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127 <expand macro="max_iter" default_value="200"/> |
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128 <param argument="convergence_iter" type="integer" optional="true" value="15" label="Number of iterations at each convergence step" help="Number of iterations with no change in the number of estimated clusters that stops the convergence."/> |
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129 <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Copy" help="If False, the affinity matrix is modified inplace by the algorithm, for memory efficiency."/> |
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130 <!--param argument="preference"/--> |
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131 <param argument="affinity" type="select" label="Affinity" help="Affinity to use; euclidean uses the negative squared euclidean distance between points."> |
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132 <option value="euclidean">Euclidean</option> |
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133 <option value="precomputed">precomputed</option> |
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134 </param> |
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135 </section> |
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136 </when> |
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137 <when value="MeanShift"> |
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138 <section name="options" title="Advanced Options" expanded="False"> |
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139 <param argument="bandwidth" type="float" optional="true" value="" label="Kernel bandwidth" help="Bandwidth used in the RBF kernel. If not given, it will be computed using a heuristic based on the median of all pairwise distances."/> |
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140 <!--param argument="seeds"/--> |
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141 <param argument="bin_seeding" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Discretize initial kernel locations" help="If true, initial kernel locations are the bins grid whose coarseness corresponds to the bandwidth, speeding up the algorithm."/> |
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142 <param argument="min_bin_freq" type="integer" optional="true" value="1" label="Minimum number of seeds per bin" help="To speed up the algorithm, accept only those bins with at least min_bin_freq points as seeds."/> |
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143 <param argument="cluster_all" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Cluster all" help="If true, all points (including orphans) are clustered. If false, orphans are given cluster label -1."/> |
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144 </section> |
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145 </when> |
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146 <when value="AgglomerativeClustering"> |
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147 <section name="options" title="Advanced Options" expanded="False"> |
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148 <expand macro="n_clusters" default_value="2" /> |
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149 <param argument="affinity" type="select" label="Affinity" help="Metric used to compute the linkage. If linkage is ''ward'', only ''euclidean'' is accepted."> |
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150 <option value="euclidean">Euclidean</option> |
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151 <option value="manhattan">Manhattan</option> |
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152 <option value="l1">L1</option> |
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153 <option value="l2">L2</option> |
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154 <option value="cosine">cosine</option> |
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155 <option value="precomputed">precomputed</option> |
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156 </param> |
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157 <!--param argument="memory"--> |
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158 <!--param argument="connectivity"--> |
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159 <!--param argument="n_components"/--> |
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160 <!--param argument="compute_full_tree"--> |
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161 <param argument="linkage" type="select" optional="true" label="Linkage" help=""> |
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162 <option value="ward" selected="true">ward</option> |
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163 <option value="complete">complete</option> |
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164 <option value="average">average</option> |
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165 </param> |
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166 <!--param argument="pooling_func"--> |
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167 </section> |
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168 </when> |
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169 </conditional> |
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170 </when> |
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171 </conditional> |
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172 </inputs> |
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173 <outputs> |
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174 <data format="tabular" name="outfile"/> |
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175 </outputs> |
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176 <tests> |
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177 <test> |
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178 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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179 <param name="selected_input_type" value="tabular"/> |
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180 <param name="selected_algorithm" value="KMeans"/> |
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181 <param name="col" value="2,3,4" /> |
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0
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182 <param name="n_clusters" value="4" /> |
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183 <param name="init" value="k-means++" /> |
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184 <param name="random_state" value="100"/> |
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185 <output name="outfile" file="cluster_result01.txt"/> |
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186 </test> |
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187 <test> |
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188 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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189 <param name="selected_algorithm" value="KMeans"/> |
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190 <param name="selected_input_type" value="tabular"/> |
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13
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191 <param name="col" value="2,3,4" /> |
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0
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192 <param name="n_clusters" value="4" /> |
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193 <param name="init" value="random" /> |
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194 <param name="random_state" value="100"/> |
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195 <output name="outfile" file="cluster_result02.txt"/> |
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196 </test> |
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197 <test> |
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198 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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199 <param name="selected_algorithm" value="DBSCAN"/> |
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200 <param name="selected_input_type" value="tabular"/> |
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13
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201 <param name="col" value="2,3,4" /> |
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0
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202 <param name="algorithm" value="kd_tree"/> |
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203 <param name="leaf_size" value="10"/> |
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204 <param name="eps" value="1.0"/> |
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205 <output name="outfile" file="cluster_result03.txt"/> |
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206 </test> |
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207 <test> |
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208 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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209 <param name="selected_algorithm" value="Birch"/> |
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210 <param name="selected_input_type" value="tabular"/> |
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13
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211 <param name="col" value="2,3,4" /> |
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0
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212 <param name="n_clusters" value="4"/> |
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213 <param name="threshold" value="0.008"/> |
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214 <output name="outfile" file="cluster_result04.txt"/> |
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215 </test> |
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216 <test> |
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217 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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218 <param name="selected_algorithm" value="Birch"/> |
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219 <param name="selected_input_type" value="tabular"/> |
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13
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220 <param name="col" value="2,3,4" /> |
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0
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221 <param name="branching_factor" value="20"/> |
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222 <output name="outfile" file="cluster_result05.txt"/> |
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223 </test> |
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224 <test> |
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225 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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226 <param name="selected_algorithm" value="AffinityPropagation"/> |
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227 <param name="selected_input_type" value="tabular"/> |
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13
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228 <param name="col" value="2,3,4" /> |
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0
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229 <param name="affinity" value="euclidean"/> |
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230 <param name="copy" value="false"/> |
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231 <output name="outfile" file="cluster_result06.txt"/> |
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232 </test> |
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233 <test> |
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234 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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235 <param name="selected_algorithm" value="AffinityPropagation"/> |
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236 <param name="selected_input_type" value="tabular"/> |
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13
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237 <param name="col" value="2,3,4" /> |
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0
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238 <param name="damping" value="0.8"/> |
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239 <output name="outfile" file="cluster_result07.txt"/> |
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c7b8fab00c0f
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240 </test> |
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241 <test> |
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242 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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c7b8fab00c0f
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243 <param name="selected_algorithm" value="MeanShift"/> |
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c7b8fab00c0f
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244 <param name="selected_input_type" value="tabular"/> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
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245 <param name="col" value="2,3,4" /> |
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0
c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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246 <param name="min_bin_freq" value="3"/> |
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c7b8fab00c0f
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247 <output name="outfile" file="cluster_result08.txt"/> |
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c7b8fab00c0f
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248 </test> |
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249 <test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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250 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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251 <param name="selected_algorithm" value="MeanShift"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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252 <param name="selected_input_type" value="tabular"/> |
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13
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
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253 <param name="col" value="2,3,4" /> |
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0
c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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254 <param name="cluster_all" value="False"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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255 <output name="outfile" file="cluster_result09.txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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256 </test> |
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257 <test> |
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c7b8fab00c0f
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258 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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259 <param name="selected_algorithm" value="AgglomerativeClustering"/> |
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c7b8fab00c0f
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260 <param name="selected_input_type" value="tabular"/> |
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13
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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261 <param name="col" value="2,3,4" /> |
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0
c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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262 <param name="affinity" value="euclidean"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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263 <param name="linkage" value="average"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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264 <param name="n_clusters" value="4"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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265 <output name="outfile" file="cluster_result10.txt"/> |
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c7b8fab00c0f
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266 </test> |
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267 <test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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268 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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269 <param name="selected_algorithm" value="AgglomerativeClustering"/> |
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c7b8fab00c0f
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270 <param name="selected_input_type" value="tabular"/> |
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13
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271 <param name="col" value="2,3,4" /> |
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0
c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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272 <param name="linkage" value="complete"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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273 <param name="n_clusters" value="4"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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274 <output name="outfile" file="cluster_result11.txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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275 </test> |
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276 <test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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277 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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278 <param name="selected_algorithm" value="SpectralClustering"/> |
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c7b8fab00c0f
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279 <param name="selected_input_type" value="tabular"/> |
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13
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280 <param name="col" value="2,3,4" /> |
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0
c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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281 <param name="eigen_solver" value="arpack"/> |
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c7b8fab00c0f
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282 <param name="n_neighbors" value="12"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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283 <param name="n_clusters" value="4"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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284 <param name="assign_labels" value="discretize"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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285 <param name="random_state" value="100"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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286 <output name="outfile" file="cluster_result12" compare="sim_size" /> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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287 </test> |
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288 <test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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289 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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290 <param name="selected_algorithm" value="SpectralClustering"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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291 <param name="selected_input_type" value="tabular"/> |
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13
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292 <param name="col" value="2,3,4" /> |
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0
c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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293 <param name="assign_labels" value="discretize"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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294 <param name="random_state" value="100"/> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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295 <param name="degree" value="2"/> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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296 <output name="outfile" file="cluster_result13.txt" compare="sim_size" /> |
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c7b8fab00c0f
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297 </test> |
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298 <test> |
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c7b8fab00c0f
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299 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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300 <param name="selected_algorithm" value="MiniBatchKMeans"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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301 <param name="selected_input_type" value="tabular"/> |
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13
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302 <param name="col" value="2,3,4" /> |
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0
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303 <param name="tol" value="0.5"/> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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304 <param name="random_state" value="100"/> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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305 <output name="outfile" file="cluster_result14.txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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306 </test> |
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307 <test> |
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c7b8fab00c0f
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308 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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309 <param name="selected_algorithm" value="MiniBatchKMeans"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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310 <param name="selected_input_type" value="tabular"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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311 <param name="n_init" value="5"/> |
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13
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bgruening
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312 <param name="col" value="2,3,4" /> |
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0
c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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313 <param name="batch_size" value="10"/> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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314 <param name="n_clusters" value="4"/> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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315 <param name="random_state" value="100"/> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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316 <param name="reassignment_ratio" value="1.0"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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317 <output name="outfile" file="cluster_result15.txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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318 </test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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319 <test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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320 <param name="infile" value="numeric_values.tabular" ftype="tabular"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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321 <param name="selected_algorithm" value="KMeans"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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322 <param name="selected_input_type" value="tabular"/> |
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13
40f3318b61c2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
bgruening
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323 <param name="col" value="1" /> |
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0
c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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324 <param name="n_clusters" value="4" /> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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325 <param name="random_state" value="100"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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326 <output name="outfile" file="cluster_result16.txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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327 </test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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328 <test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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329 <param name="infile" value="sparse.mtx" ftype="txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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330 <param name="selected_input_type" value="sparse"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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331 <param name="selected_algorithm" value="KMeans"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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332 <param name="n_clusters" value="2" /> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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333 <param name="init" value="k-means++" /> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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334 <param name="random_state" value="100"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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diff
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335 <output name="outfile" file="cluster_result17.txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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336 </test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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337 <test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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338 <param name="infile" value="sparse.mtx" ftype="txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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339 <param name="selected_algorithm" value="DBSCAN"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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340 <param name="selected_input_type" value="sparse"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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341 <param name="algorithm" value="kd_tree"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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342 <param name="leaf_size" value="10"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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343 <param name="eps" value="1.0"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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344 <output name="outfile" file="cluster_result18.txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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345 </test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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346 <test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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347 <param name="infile" value="sparse.mtx" ftype="txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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348 <param name="selected_algorithm" value="Birch"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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349 <param name="selected_input_type" value="sparse"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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350 <param name="n_clusters" value="2"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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351 <param name="threshold" value="0.008"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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352 <output name="outfile" file="cluster_result19.txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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353 </test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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354 <test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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355 <param name="infile" value="sparse.mtx" ftype="txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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356 <param name="selected_algorithm" value="MiniBatchKMeans"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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357 <param name="selected_input_type" value="sparse"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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358 <param name="n_init" value="5"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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359 <param name="batch_size" value="10"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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360 <param name="n_clusters" value="2"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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361 <param name="random_state" value="100"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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362 <param name="reassignment_ratio" value="1.0"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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363 <output name="outfile" file="cluster_result20.txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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364 </test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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365 <test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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366 <param name="infile" value="sparse.mtx" ftype="txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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367 <param name="selected_algorithm" value="SpectralClustering"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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368 <param name="selected_input_type" value="sparse"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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369 <param name="assign_labels" value="discretize"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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370 <param name="n_clusters" value="2"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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371 <param name="random_state" value="100"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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372 <param name="degree" value="2"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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373 <output name="outfile" file="cluster_result21.txt"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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374 </test> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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375 </tests> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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376 <help><![CDATA[ |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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377 **What it does** |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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378 This tool offers different clustering algorithms which are provided by |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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379 scikit-learn to find similarities among samples and cluster the samples based on these similarities. |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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380 ]]></help> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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381 <expand macro="sklearn_citation"/> |
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c7b8fab00c0f
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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382 </tool> |