Mercurial > repos > bgruening > sklearn_generalized_linear
annotate generalized_linear.xml @ 28:63417d0acc72 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
author | bgruening |
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date | Wed, 02 Oct 2019 03:43:23 -0400 |
parents | 9d3a024cf2da |
children | a8c7b9fa426c |
rev | line source |
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0
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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1 <tool id="sklearn_generalized_linear" name="Generalized linear models" version="@VERSION@"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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2 <description>for classification and regression</description> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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3 <macros> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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4 <import>main_macros.xml</import> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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5 </macros> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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6 <expand macro="python_requirements"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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7 <expand macro="macro_stdio"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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8 <version_command>echo "@VERSION@"</version_command> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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9 <command><![CDATA[ |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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10 python "$glm_script" '$inputs' |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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11 ]]> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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12 </command> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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13 <configfiles> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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14 <inputs name="inputs"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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15 <configfile name="glm_script"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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16 <![CDATA[ |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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17 import sys |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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18 import json |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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19 import numpy as np |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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20 import sklearn.linear_model |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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21 import pandas |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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22 import pickle |
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32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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23 |
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9d3a024cf2da
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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24 from scipy.io import mmread |
9d3a024cf2da
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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25 from galaxy_ml.utils import load_model, get_X_y |
9d3a024cf2da
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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26 |
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32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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27 |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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28 input_json_path = sys.argv[1] |
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f0e215cbade3
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48
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29 with open(input_json_path, "r") as param_handler: |
f0e215cbade3
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48
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30 params = json.load(param_handler) |
0
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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31 |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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32 #if $selected_tasks.selected_task == "train": |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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33 |
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cf635edf37d2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
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34 X, y = get_X_y(params, "$selected_tasks.selected_algorithms.input_options.infile1" ,"$selected_tasks.selected_algorithms.input_options.infile2") |
cf635edf37d2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
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35 |
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32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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36 algorithm = params["selected_tasks"]["selected_algorithms"]["selected_algorithm"] |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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37 options = params["selected_tasks"]["selected_algorithms"]["options"] |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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38 |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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39 my_class = getattr(sklearn.linear_model, algorithm) |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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40 estimator = my_class(**options) |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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41 estimator.fit(X,y) |
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f0e215cbade3
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48
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42 with open("$outfile_fit", 'wb') as out_handler: |
f0e215cbade3
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48
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43 pickle.dump(estimator, out_handler, pickle.HIGHEST_PROTOCOL) |
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32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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44 |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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45 #else: |
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f0e215cbade3
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48
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46 with open("$selected_tasks.infile_model", 'rb') as model_handler: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2a058459e6daf0486871f93845f00fdb4a4eaca1
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47 classifier_object = load_model(model_handler) |
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63417d0acc72
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
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48 header = 'infer' if params["selected_tasks"]["header"] else None |
63417d0acc72
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
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49 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False) |
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32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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50 prediction = classifier_object.predict(data) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 7c2fd140e89605fe689c39e21d70a400545e38cf
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51 prediction_df = pandas.DataFrame(prediction, columns=["predicted"]) |
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32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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52 res = pandas.concat([data, prediction_df], axis=1) |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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53 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False, header=None) |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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54 #end if |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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55 |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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56 ]]> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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57 </configfile> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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58 </configfiles> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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59 <inputs> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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60 <expand macro="sl_Conditional" model="zip"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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61 <param name="selected_algorithm" type="select" label="Select a linear model:"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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62 <option value="SGDClassifier" selected="true">Stochastic Gradient Descent (SGD) classifier</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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63 <option value="SGDRegressor">Stochastic Gradient Descent (SGD) regressor</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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64 <option value="LinearRegression">Linear Regression model</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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65 <option value="RidgeClassifier">Ridge classifier</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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66 <option value="Ridge">Ridge regressor</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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67 <option value="LogisticRegression">Logistic Regression</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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68 <option value="LogisticRegressionCV">Logitic Regression with Cross Validation</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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69 <option value="Perceptron">Perceptron</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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70 </param> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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71 <when value="SGDClassifier"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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72 <expand macro="sl_mixed_input"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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73 <section name="options" title="Advanced Options" expanded="False"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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74 <expand macro="loss"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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75 <option value="hinge" selected="true">hinge</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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76 <option value="log">log</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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77 <option value="modified_huber">modified huber</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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78 <option value="squared_hinge">squared hinge</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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79 <option value="perceptron">perceptron</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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80 </expand> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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81 <expand macro="penalty"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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82 <expand macro="alpha"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
|
83 <expand macro="l1_ratio"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
|
84 <expand macro="fit_intercept"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
|
85 <expand macro="n_iter" /> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
|
86 <expand macro="shuffle"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
|
87 <expand macro="epsilon"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
|
88 <expand macro="learning_rate_s" selected1="true"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
|
89 <expand macro="eta0"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
|
90 <expand macro="power_t"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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diff
changeset
|
91 <!--class_weight--> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
|
92 <expand macro="warm_start" checked="false"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
|
93 <expand macro="random_state"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
|
94 <!--average--> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
|
95 </section> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
|
96 </when> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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97 <when value="SGDRegressor"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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98 <expand macro="sl_mixed_input"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
|
99 <section name="options" title="Advanced Options" expanded="False"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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100 <expand macro="loss" select="true"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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101 <expand macro="penalty"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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102 <expand macro="alpha"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
|
103 <expand macro="l1_ratio"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
|
104 <expand macro="fit_intercept"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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diff
changeset
|
105 <expand macro="n_iter" /> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
|
106 <expand macro="shuffle"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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|
107 <expand macro="epsilon"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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108 <expand macro="learning_rate_s" selected2="true"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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109 <expand macro="eta0" default_value="0.01"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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110 <expand macro="power_t" default_value="0.25"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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111 <expand macro="warm_start" checked="false"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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112 <expand macro="random_state"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
|
113 <!--average--> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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114 </section> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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115 </when> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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116 <when value="LinearRegression"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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117 <expand macro="sl_mixed_input"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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118 <section name="options" title="Advanced Options" expanded="False"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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119 <expand macro="fit_intercept"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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120 <expand macro="normalize"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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121 <expand macro="copy_X"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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|
122 </section> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
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123 </when> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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124 <when value="RidgeClassifier"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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125 <expand macro="sl_mixed_input"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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126 <section name="options" title="Advanced Options" expanded="False"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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127 <expand macro="ridge_params"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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128 </section> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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129 </when> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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130 <when value="Ridge"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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131 <expand macro="sl_mixed_input"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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132 <section name="options" title="Advanced Options" expanded="False"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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133 <expand macro="ridge_params"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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134 </section> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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135 </when> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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|
136 <when value="LogisticRegression"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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137 <expand macro="sl_mixed_input"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
|
138 <section name="options" title="Advanced Options" expanded="False"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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139 <expand macro="penalty"/> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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140 <param argument="dual" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Use dual formulation" help=" "/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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141 <expand macro="tol" default_value="0.0001" help_text="Tolerance for stopping criteria. "/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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142 <expand macro="C"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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143 <expand macro="fit_intercept"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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144 <expand macro="max_iter" default_value="100"/> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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145 <expand macro="warm_start" checked="false"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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146 <param argument="solver" type="select" label="Optimization algorithm" help=" "> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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147 <option value="liblinear" selected="true">liblinear</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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148 <option value="sag">sag</option> |
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149 <option value="lbfgs">lbfgs</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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150 <option value="newton-cg">newton-cg</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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151 </param> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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152 <param argument="intercept_scaling" type="float" value="1" label="Intercept scaling factor" help="Useful only if solver is liblinear. "/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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153 <param argument="multi_class" type="select" label="Multiclass option" help="Works only for lbfgs solver. "> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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154 <option value="ovr" selected="true">ovr</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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155 <option value="multinomial">multinomial</option> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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156 </param> |
32a88b3bea94
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157 <!--class_weight--> |
32a88b3bea94
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158 <expand macro="random_state"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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159 </section> |
32a88b3bea94
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bgruening
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160 </when> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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161 <when value="LogisticRegressionCV"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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162 <expand macro="sl_mixed_input"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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163 <section name="options" title="Advanced Options" expanded="False"> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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164 <param argument="Cs" type="integer" value="10" label="Inverse of regularization strength" help="A grid of Cs values are chosen in a logarithmic scale between 1e-4 and 1e4. Like in support vector machines, smaller values specify stronger regularization. "/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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165 <param argument="dual" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Use dual formulation" help=" "/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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166 <param argument="cv" type="integer" optional="true" value="" label="Number of folds used in cross validation" help="If not set, the default cross-validation generator (Stratified K-Folds) is used. "/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
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167 <expand macro="penalty"/> |
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168 <expand macro="tol" default_value="0.0001" help_text="Tolerance for stopping criteria. "/> |
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169 <expand macro="fit_intercept"/> |
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170 <expand macro="max_iter" default_value="100"/> |
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171 <param argument="solver" type="select" label="Optimization algorithm" help=" "> |
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172 <option value="liblinear" selected="true">liblinear</option> |
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173 <option value="sag">sag</option> |
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174 <option value="lbfgs">lbfgs</option> |
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175 <option value="newton-cg">newton-cg</option> |
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176 </param> |
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177 <param argument="intercept_scaling" type="float" value="1" label="Intercept scaling factor" help="Useful only if solver is liblinear. "/> |
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178 <param argument="multi_class" type="select" label="Multiclass option" help="Works only for lbfgs solver. "> |
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179 <option value="ovr" selected="true">ovr</option> |
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180 <option value="multinomial">multinomial</option> |
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181 </param> |
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182 <param argument="refit" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" label="Average scores across all folds" help=" "/> |
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183 <expand macro="random_state"/> |
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184 <!--scoring=None> |
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185 <class_weight=None--> |
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186 </section> |
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187 </when> |
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188 <when value="Perceptron"> |
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189 <expand macro="sl_mixed_input"/> |
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190 <section name="options" title="Advanced Options" expanded="False"> |
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191 <expand macro="penalty" default_value="none"/> |
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192 <expand macro="alpha"/> |
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193 <expand macro="fit_intercept"/> |
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194 <expand macro="n_iter" /> |
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195 <expand macro="shuffle"/> |
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196 <expand macro="eta0" default_value="1"/> |
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197 <expand macro="warm_start" checked="false"/> |
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198 <expand macro="random_state" default_value="0"/> |
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199 <!--class_weight=None--> |
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200 </section> |
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201 </when> |
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202 </expand> |
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203 </inputs> |
21
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20
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204 <expand macro="output"/> |
0
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205 <tests> |
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206 <test> |
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207 <param name="infile1" value="regression_train.tabular" ftype="tabular"/> |
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208 <param name="infile2" value="regression_train.tabular" ftype="tabular"/> |
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209 <param name="selected_column_selector_option" value="all_but_by_index_number"/> |
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210 <param name="col1" value="6"/> |
0
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211 <param name="col2" value="6"/> |
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212 <param name="selected_task" value="train"/> |
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213 <param name="selected_algorithm" value="SGDRegressor"/> |
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214 <param name="random_state" value="10"/> |
23
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diff
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215 <output name="outfile_fit" file="glm_model01" compare="sim_size" delta="5"/> |
0
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216 </test> |
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217 <test> |
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218 <param name="infile_model" value="glm_model01" ftype="zip"/> |
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219 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/> |
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220 <param name="selected_task" value="load"/> |
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221 <output name="outfile_predict" file="glm_result01" lines_diff="4"/> |
0
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222 </test> |
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223 <test> |
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224 <param name="infile1" value="train.tabular" ftype="tabular"/> |
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225 <param name="infile2" value="train.tabular" ftype="tabular"/> |
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226 <param name="col1" value="1,2,3,4"/> |
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227 <param name="col2" value="5"/> |
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228 <param name="selected_task" value="train"/> |
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229 <param name="selected_algorithm" value="SGDClassifier"/> |
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230 <param name="random_state" value="10"/> |
23
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231 <output name="outfile_fit" file="glm_model02" compare="sim_size" delta="5"/> |
0
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232 </test> |
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233 <test> |
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234 <param name="infile_model" value="glm_model02" ftype="zip"/> |
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235 <param name="infile_data" value="test.tabular" ftype="tabular"/> |
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236 <param name="selected_task" value="load"/> |
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237 <output name="outfile_predict" file="glm_result02"/> |
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238 </test> |
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239 <test> |
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240 <param name="infile1" value="train.tabular" ftype="tabular"/> |
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241 <param name="infile2" value="train.tabular" ftype="tabular"/> |
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242 <param name="col1" value="1,2,3,4"/> |
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243 <param name="col2" value="5"/> |
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244 <param name="selected_task" value="train"/> |
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245 <param name="selected_algorithm" value="RidgeClassifier"/> |
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246 <param name="random_state" value="10"/> |
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247 <output name="outfile_fit" file="glm_model03" compare="sim_size" delta="5"/> |
0
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248 </test> |
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249 <test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
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250 <param name="infile_model" value="glm_model03" ftype="zip"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
|
251 <param name="infile_data" value="test.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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changeset
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252 <param name="selected_task" value="load"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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changeset
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253 <output name="outfile_predict" file="glm_result03"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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changeset
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254 </test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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changeset
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255 <test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
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256 <param name="infile1" value="regression_train.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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changeset
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257 <param name="infile2" value="regression_train.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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258 <param name="col1" value="1,2,3,4,5"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff
changeset
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259 <param name="col2" value="6"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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260 <param name="selected_task" value="train"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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261 <param name="selected_algorithm" value="LinearRegression"/> |
23
e3bc646e63b2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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diff
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262 <output name="outfile_fit" file="glm_model04" compare="sim_size" delta="5"/> |
0
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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263 </test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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changeset
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264 <test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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diff
changeset
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265 <param name="infile_model" value="glm_model04" ftype="zip"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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266 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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267 <param name="selected_task" value="load"/> |
23
e3bc646e63b2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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268 <output name="outfile_predict" file="glm_result04" lines_diff="8"/> |
0
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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269 </test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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270 <test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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271 <param name="infile1" value="train.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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272 <param name="infile2" value="train.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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273 <param name="col1" value="1,2,3,4"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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274 <param name="col2" value="5"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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275 <param name="selected_task" value="train"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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276 <param name="selected_algorithm" value="LogisticRegression"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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277 <param name="random_state" value="10"/> |
23
e3bc646e63b2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
bgruening
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278 <output name="outfile_fit" file="glm_model05" compare="sim_size" delta="5"/> |
0
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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279 </test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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280 <test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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281 <param name="infile_model" value="glm_model05" ftype="zip"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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282 <param name="infile_data" value="test.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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283 <param name="selected_task" value="load"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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284 <output name="outfile_predict" file="glm_result05"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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285 </test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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286 <test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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287 <param name="infile1" value="train.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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288 <param name="infile2" value="train.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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289 <param name="col1" value="1,2,3,4"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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changeset
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290 <param name="col2" value="5"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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291 <param name="selected_task" value="train"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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292 <param name="selected_algorithm" value="LogisticRegressionCV"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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293 <param name="random_state" value="10"/> |
23
e3bc646e63b2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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294 <output name="outfile_fit" file="glm_model06" compare="sim_size" delta="5"/> |
0
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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295 </test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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296 <test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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297 <param name="infile_model" value="glm_model06" ftype="zip"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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298 <param name="infile_data" value="test.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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299 <param name="selected_task" value="load"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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300 <output name="outfile_predict" file="glm_result06"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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301 </test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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302 <test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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303 <param name="infile1" value="regression_train.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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304 <param name="infile2" value="regression_train.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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305 <param name="col1" value="1,2,3,4,5"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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306 <param name="col2" value="6"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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307 <param name="selected_task" value="train"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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308 <param name="selected_algorithm" value="Ridge"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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309 <param name="random_state" value="10"/> |
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e3bc646e63b2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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310 <output name="outfile_fit" file="glm_model07" compare="sim_size" delta="5"/> |
0
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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311 </test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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312 <test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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313 <param name="infile_model" value="glm_model07" ftype="zip"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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314 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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315 <param name="selected_task" value="load"/> |
23
e3bc646e63b2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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316 <output name="outfile_predict" file="glm_result07"/> |
0
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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317 </test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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318 <test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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319 <param name="infile1" value="train.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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320 <param name="infile2" value="train.tabular" ftype="tabular"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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321 <param name="col1" value="1,2,3,4"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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changeset
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322 <param name="col2" value="5"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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323 <param name="selected_task" value="train"/> |
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e0f8931f6149
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c64ccc5850c8e061a95fb64e07ed388384e82393
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324 <param name="selected_algorithm" value="Perceptron"/> |
0
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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325 <param name="random_state" value="10"/> |
23
e3bc646e63b2
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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326 <output name="outfile_fit" file="glm_model08" compare="sim_size" delta="5"/> |
0
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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327 </test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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328 <test> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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329 <param name="infile_model" value="glm_model08" ftype="zip"/> |
32a88b3bea94
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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330 <param name="infile_data" value="test.tabular" ftype="tabular"/> |
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331 <param name="selected_task" value="load"/> |
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332 <output name="outfile_predict" file="glm_result08"/> |
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333 </test> |
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334 </tests> |
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335 <help><![CDATA[ |
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336 ***What it does*** |
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337 This module implements a set of linear models for classification and regression such as: SGD classification and regression, Linear and Ridge regression and classification. This wrapper is using sklearn.linear_model module at its core. For information about linear models and their parameter settings please refer to `Scikit-learn generalized linear models`_. |
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338 |
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339 .. _`Scikit-learn generalized linear models`: http://scikit-learn.org/stable/modules/linear_model.html |
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340 |
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341 **1 - Methods** |
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342 There are two groups of operations available: |
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343 |
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344 1 - Train a model : A training set containing samples and their respective labels (or predicted values) are input. Based on the selected algorithm and options, an estimator object is fit to the data and is returned. |
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345 |
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346 2 - Load a model and predict : An existing model predicts the class labels (or regression values) for a new dataset. |
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347 |
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348 **2 - Trainig input** |
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349 When you choose to train a model, you need a features dataset X and a labels set y. This tool expects tabular or sparse data for X and a single column for y (tabular). You can select a subset of columns in a tabular dataset as your features dataset or labels column. Below you find some examples: |
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350 |
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351 **Sample tabular features dataset** |
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352 The following training dataset contains 3 feature columns and a column containing class labels. You can simply select the first 3 columns as features and the last column as labels: |
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353 |
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354 :: |
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355 |
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356 4.01163365529 -6.10797684314 8.29829894763 1 |
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357 10.0788438916 1.59539821454 10.0684278289 0 |
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358 -5.17607775503 -0.878286135332 6.92941850665 2 |
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359 4.00975406235 -7.11847496542 9.3802423585 1 |
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360 4.61204065139 -5.71217537352 9.12509610964 1 |
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361 |
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362 |
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363 **Sample sparse features dataset** |
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364 In this case you cannot specifiy a column range. |
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365 |
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366 :: |
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367 |
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368 4 1048577 8738 |
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369 1 271 0.020833 |
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370 1 1038 0.02461 |
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371 2 829017 0.016 |
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372 2 829437 0.012 |
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373 2 830752 0.025 |
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374 3 1047487 0.01 |
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375 3 1047980 0.02 |
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376 3 1048475 0.01 |
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377 4 608 0.016629 |
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378 4 1651 0.02519 |
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379 4 4053 0.04223 |
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380 |
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381 |
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382 **2 - Trainig output** |
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383 The trained model is generated and output in the form of a binary file. |
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384 |
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385 |
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386 **3 - Prediction input** |
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387 |
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388 When you choose to load a model and do prediction, the tool expects an already trained estimator and a tabular dataset as input. The dataset contains new samples which you want to classify or predict regression values for. |
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389 |
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390 |
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391 .. class:: warningmark |
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392 |
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393 The number of feature columns must be the same in training and prediction datasets! |
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394 |
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395 |
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396 **3 - Prediction output** |
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397 The tool predicts the class labels for new samples and adds them as the last column to the prediction dataset. The new dataset then is output as a tabular file. The prediction output format should look like the training dataset. |
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398 |
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399 ]]></help> |
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400 <expand macro="sklearn_citation"/> |
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401 </tool> |