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comparison main_macros.xml @ 16:b9377256bac7 draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
author bgruening
date Sat, 04 Aug 2018 12:30:53 -0400
parents f02f05990cc9
children 5d98b35a807e
comparison
equal deleted inserted replaced
15:f02f05990cc9 16:b9377256bac7
32 options = inputs["options"] 32 options = inputs["options"]
33 33
34 if inputs['selected_algorithm'] == 'SelectFromModel': 34 if inputs['selected_algorithm'] == 'SelectFromModel':
35 if not options['threshold'] or options['threshold'] == 'None': 35 if not options['threshold'] or options['threshold'] == 'None':
36 options['threshold'] = None 36 options['threshold'] = None
37 if 'extra_estimator' in inputs and inputs['extra_estimator']['has_estimator'] == 'no_load': 37 if inputs['model_inputter']['input_mode'] == 'prefitted':
38 with open("inputs['extra_estimator']['fitted_estimator']", 'rb') as model_handler: 38 model_file = inputs['model_inputter']['fitted_estimator']
39 fitted_estimator = pickle.load(model_handler) 39 with open(model_file, 'rb') as model_handler:
40 new_selector = selector(fitted_estimator, prefit=True, **options) 40 fitted_estimator = pickle.load(model_handler)
41 else: 41 new_selector = selector(fitted_estimator, prefit=True, **options)
42 estimator=inputs["estimator"] 42 else:
43 if inputs["extra_estimator"]["has_estimator"]=='no': 43 estimator_json = inputs['model_inputter']["estimator_selector"]
44 estimator=inputs["extra_estimator"]["new_estimator"] 44 estimator = get_estimator(estimator_json)
45 estimator=eval(estimator.replace('__dq__', '"').replace("__sq__","'")) 45 new_selector = selector(estimator, **options)
46 new_selector = selector(estimator, **options)
47 46
48 elif inputs['selected_algorithm'] in ['RFE', 'RFECV']: 47 elif inputs['selected_algorithm'] in ['RFE', 'RFECV']:
49 if 'scoring' in options and (not options['scoring'] or options['scoring'] == 'None'): 48 if 'scoring' in options and (not options['scoring'] or options['scoring'] == 'None'):
50 options['scoring'] = None 49 options['scoring'] = None
51 estimator=inputs["estimator"] 50 estimator=get_estimator(inputs["estimator_selector"])
52 if inputs["extra_estimator"]["has_estimator"]=='no':
53 estimator=inputs["extra_estimator"]["new_estimator"]
54 estimator=eval(estimator.replace('__dq__', '"').replace("__sq__","'"))
55 new_selector = selector(estimator, **options) 51 new_selector = selector(estimator, **options)
56 52
57 elif inputs['selected_algorithm'] == "VarianceThreshold": 53 elif inputs['selected_algorithm'] == "VarianceThreshold":
58 new_selector = selector(**options) 54 new_selector = selector(**options)
59 55
102 ) 98 )
103 y=y.ravel() 99 y=y.ravel()
104 return X, y 100 return X, y
105 </token> 101 </token>
106 102
103 <token name="@GET_SEARCH_PARAMS_FUNCTION@">
104 def get_search_params(params_builder):
105 search_params = {}
106
107 def safe_eval(literal):
108
109 FROM_SCIPY_STATS = [ 'bernoulli', 'binom', 'boltzmann', 'dlaplace', 'geom', 'hypergeom',
110 'logser', 'nbinom', 'planck', 'poisson', 'randint', 'skellam', 'zipf' ]
111
112 FROM_NUMPY_RANDOM = [ 'beta', 'binomial', 'bytes', 'chisquare', 'choice', 'dirichlet', 'division',
113 'exponential', 'f', 'gamma', 'geometric', 'gumbel', 'hypergeometric',
114 'laplace', 'logistic', 'lognormal', 'logseries', 'mtrand', 'multinomial',
115 'multivariate_normal', 'negative_binomial', 'noncentral_chisquare', 'noncentral_f',
116 'normal', 'pareto', 'permutation', 'poisson', 'power', 'rand', 'randint',
117 'randn', 'random', 'random_integers', 'random_sample', 'ranf', 'rayleigh',
118 'sample', 'seed', 'set_state', 'shuffle', 'standard_cauchy', 'standard_exponential',
119 'standard_gamma', 'standard_normal', 'standard_t', 'triangular', 'uniform',
120 'vonmises', 'wald', 'weibull', 'zipf' ]
121
122 # File opening and other unneeded functions could be dropped
123 UNWANTED = ['open', 'type', 'dir', 'id', 'str', 'repr']
124
125 # Allowed symbol table. Add more if needed.
126 new_syms = {
127 'np_arange': getattr(np, 'arange'),
128 'ensemble_ExtraTreesClassifier': getattr(ensemble, 'ExtraTreesClassifier')
129 }
130
131 syms = make_symbol_table(use_numpy=False, **new_syms)
132
133 for method in FROM_SCIPY_STATS:
134 syms['scipy_stats_' + method] = getattr(scipy.stats, method)
135
136 for func in FROM_NUMPY_RANDOM:
137 syms['np_random_' + func] = getattr(np.random, func)
138
139 for key in UNWANTED:
140 syms.pop(key, None)
141
142 aeval = Interpreter(symtable=syms, use_numpy=False, minimal=False,
143 no_if=True, no_for=True, no_while=True, no_try=True,
144 no_functiondef=True, no_ifexp=True, no_listcomp=False,
145 no_augassign=False, no_assert=True, no_delete=True,
146 no_raise=True, no_print=True)
147
148 return aeval(literal)
149
150 for p in params_builder['param_set']:
151 search_p = p['search_param_selector']['search_p']
152 if search_p.strip() == '':
153 continue
154 param_type = p['search_param_selector']['selected_param_type']
155
156 lst = search_p.split(":")
157 assert (len(lst) == 2), "Error, make sure there is one and only one colon in search parameter input."
158 literal = lst[1].strip()
159 ev = safe_eval(literal)
160 if param_type == "final_estimator_p":
161 search_params["estimator__" + lst[0].strip()] = ev
162 else:
163 search_params["preprocessing_" + param_type[5:6] + "__" + lst[0].strip()] = ev
164
165 return search_params
166 </token>
167
168 <token name="@GET_ESTIMATOR_FUNCTION@">
169 def get_estimator(estimator_json):
170 estimator_module = estimator_json['selected_module']
171 estimator_cls = estimator_json['selected_estimator']
172
173 if estimator_module == "xgboost":
174 cls = getattr(xgboost, estimator_cls)
175 else:
176 module = getattr(sklearn, estimator_module)
177 cls = getattr(module, estimator_cls)
178
179 estimator = cls()
180
181 estimator_params = estimator_json['text_params'].strip()
182 if estimator_params != "":
183 try:
184 params = ast.literal_eval('{' + estimator_params + '}')
185 except ValueError:
186 sys.exit("Unsupported parameter input: `%s`" %estimator_params)
187 estimator.set_params(**params)
188
189 return estimator
190 </token>
191
107 <xml name="python_requirements"> 192 <xml name="python_requirements">
108 <requirements> 193 <requirements>
109 <requirement type="package" version="2.7">python</requirement> 194 <requirement type="package" version="2.7">python</requirement>
110 <requirement type="package" version="0.19.1">scikit-learn</requirement> 195 <requirement type="package" version="0.19.1">scikit-learn</requirement>
111 <requirement type="package" version="0.22.0">pandas</requirement> 196 <requirement type="package" version="0.22.0">pandas</requirement>
197 <requirement type="package" version="0.72.1">xgboost</requirement>
112 <yield /> 198 <yield />
113 </requirements> 199 </requirements>
114 </xml> 200 </xml>
115 201
116 <xml name="macro_stdio"> 202 <xml name="macro_stdio">
905 </section> 991 </section>
906 </when> 992 </when>
907 </expand> 993 </expand>
908 </xml> 994 </xml>
909 995
910 <xml name="estimator_input_no_fit"> 996 <xml name="fs_selectfrommodel_prefitted">
911 <expand macro="feature_selection_estimator" /> 997 <param name="input_mode" type="select" label="Construct a new estimator from a selection list?" >
912 <conditional name="extra_estimator"> 998 <option value="new" selected="true">Yes</option>
913 <expand macro="feature_selection_extra_estimator" /> 999 <option value="prefitted">No. Load a prefitted estimator</option>
914 <expand macro="feature_selection_estimator_choices" /> 1000 </param>
915 </conditional> 1001 <when value="new">
1002 <expand macro="estimator_selector_all"/>
1003 </when>
1004 <when value="prefitted">
1005 <param name="fitted_estimator" type="data" format='zip' label="Load a prefitted estimator" />
1006 </when>
1007 </xml>
1008
1009 <xml name="fs_selectfrommodel_no_prefitted">
1010 <param name="input_mode" type="select" label="Construct a new estimator from a selection list?" >
1011 <option value="new" selected="true">Yes</option>
1012 </param>
1013 <when value="new">
1014 <expand macro="estimator_selector_all"/>
1015 </when>
916 </xml> 1016 </xml>
917 1017
918 <xml name="feature_selection_all"> 1018 <xml name="feature_selection_all">
919 <conditional name="feature_selection_algorithms"> 1019 <conditional name="fs_algorithm_selector">
920 <param name="selected_algorithm" type="select" label="Select a feature selection algorithm"> 1020 <param name="selected_algorithm" type="select" label="Select a feature selection algorithm">
921 <option value="SelectFromModel" selected="true">SelectFromModel - Meta-transformer for selecting features based on importance weights</option> 1021 <option value="SelectKBest" selected="true">SelectKBest - Select features according to the k highest scores</option>
922 <option value="GenericUnivariateSelect" selected="true">GenericUnivariateSelect - Univariate feature selector with configurable strategy</option> 1022 <option value="SelectFromModel">SelectFromModel - Meta-transformer for selecting features based on importance weights</option>
1023 <option value="GenericUnivariateSelect">GenericUnivariateSelect - Univariate feature selector with configurable strategy</option>
923 <option value="SelectPercentile">SelectPercentile - Select features according to a percentile of the highest scores</option> 1024 <option value="SelectPercentile">SelectPercentile - Select features according to a percentile of the highest scores</option>
924 <option value="SelectKBest">SelectKBest - Select features according to the k highest scores</option>
925 <option value="SelectFpr">SelectFpr - Filter: Select the p-values below alpha based on a FPR test</option> 1025 <option value="SelectFpr">SelectFpr - Filter: Select the p-values below alpha based on a FPR test</option>
926 <option value="SelectFdr">SelectFdr - Filter: Select the p-values for an estimated false discovery rate</option> 1026 <option value="SelectFdr">SelectFdr - Filter: Select the p-values for an estimated false discovery rate</option>
927 <option value="SelectFwe">SelectFwe - Filter: Select the p-values corresponding to Family-wise error rate</option> 1027 <option value="SelectFwe">SelectFwe - Filter: Select the p-values corresponding to Family-wise error rate</option>
928 <option value="RFE">RFE - Feature ranking with recursive feature elimination</option> 1028 <option value="RFE">RFE - Feature ranking with recursive feature elimination</option>
929 <option value="RFECV">RFECV - Feature ranking with recursive feature elimination and cross-validated selection of the best number of features</option> 1029 <option value="RFECV">RFECV - Feature ranking with recursive feature elimination and cross-validated selection of the best number of features</option>
930 <option value="VarianceThreshold">VarianceThreshold - Feature selector that removes all low-variance features</option> 1030 <option value="VarianceThreshold">VarianceThreshold - Feature selector that removes all low-variance features</option>
931 <!--option value="chi2">Compute chi-squared stats between each non-negative feature and class</option-->
932 <!--option value="f_classif">Compute the ANOVA F-value for the provided sample</option-->
933 <!--option value="f_regression">Univariate linear regression tests</option-->
934 <!--option value="mutual_info_classif">Estimate mutual information for a discrete target variable</option-->
935 <!--option value="mutual_info_regression">Estimate mutual information for a continuous target variable</option-->
936 </param> 1031 </param>
937 <when value="SelectFromModel"> 1032 <when value="SelectFromModel">
938 <expand macro="feature_selection_estimator" /> 1033 <conditional name="model_inputter">
939 <conditional name="extra_estimator"> 1034 <yield/>
940 <expand macro="feature_selection_extra_estimator" >
941 <option value="no_load">No, I will load a prefitted estimator</option>
942 </expand>
943 <expand macro="feature_selection_estimator_choices" >
944 <when value="no_load">
945 <param name="fitted_estimator" type="data" format='zip' label="Load a prefitted estimator" />
946 </when>
947 </expand>
948 </conditional> 1035 </conditional>
949 <section name="options" title="Other Options" expanded="True"> 1036 <section name="options" title="Advanced Options" expanded="False">
950 <param argument="threshold" type="text" value="" optional="true" label="threshold" help="The threshold value to use for feature selection. e.g. 'mean', 'median', '1.25*mean'." /> 1037 <param argument="threshold" type="text" value="" optional="true" label="threshold" help="The threshold value to use for feature selection. e.g. 'mean', 'median', '1.25*mean'." />
951 <param argument="norm_order" type="integer" value="1" label="norm_order" help="Order of the norm used to filter the vectors of coefficients below threshold in the case where the coef_ attribute of the estimator is of dimension 2. " /> 1038 <param argument="norm_order" type="integer" value="1" label="norm_order" help="Order of the norm used to filter the vectors of coefficients below threshold in the case where the coef_ attribute of the estimator is of dimension 2. " />
952 </section> 1039 </section>
953 </when> 1040 </when>
954 <when value="GenericUnivariateSelect"> 1041 <when value="GenericUnivariateSelect">
955 <expand macro="feature_selection_score_function" /> 1042 <expand macro="feature_selection_score_function" />
956 <section name="options" title="Other Options" expanded="True"> 1043 <section name="options" title="Advanced Options" expanded="False">
957 <param argument="mode" type="select" label="Feature selection mode"> 1044 <param argument="mode" type="select" label="Feature selection mode">
958 <option value="percentile">percentile</option> 1045 <option value="percentile">percentile</option>
959 <option value="k_best">k_best</option> 1046 <option value="k_best">k_best</option>
960 <option value="fpr">fpr</option> 1047 <option value="fpr">fpr</option>
961 <option value="fdr">fdr</option> 1048 <option value="fdr">fdr</option>
964 <param argument="param" type="float" value="" optional="true" label="Parameter of the corresponding mode" help="float or int depending on the feature selection mode" /> 1051 <param argument="param" type="float" value="" optional="true" label="Parameter of the corresponding mode" help="float or int depending on the feature selection mode" />
965 </section> 1052 </section>
966 </when> 1053 </when>
967 <when value="SelectPercentile"> 1054 <when value="SelectPercentile">
968 <expand macro="feature_selection_score_function" /> 1055 <expand macro="feature_selection_score_function" />
969 <section name="options" title="Other Options" expanded="True"> 1056 <section name="options" title="Advanced Options" expanded="False">
970 <param argument="percentile" type="integer" value="10" optional="True" label="Percent of features to keep" /> 1057 <param argument="percentile" type="integer" value="10" optional="True" label="Percent of features to keep" />
971 </section> 1058 </section>
972 </when> 1059 </when>
973 <when value="SelectKBest"> 1060 <when value="SelectKBest">
974 <expand macro="feature_selection_score_function" /> 1061 <expand macro="feature_selection_score_function" />
975 <section name="options" title="Other Options" expanded="True"> 1062 <section name="options" title="Advanced Options" expanded="False">
976 <param argument="k" type="integer" value="10" optional="True" label="Number of top features to select" help="No 'all' option is supported." /> 1063 <param argument="k" type="integer" value="10" optional="True" label="Number of top features to select" help="No 'all' option is supported." />
977 </section> 1064 </section>
978 </when> 1065 </when>
979 <when value="SelectFpr"> 1066 <when value="SelectFpr">
980 <expand macro="feature_selection_score_function" /> 1067 <expand macro="feature_selection_score_function" />
981 <section name="options" title="Other Options" expanded="True"> 1068 <section name="options" title="Advanced Options" expanded="False">
982 <param argument="alpha" type="float" value="" optional="True" label="Alpha" help="The highest p-value for features to be kept."/> 1069 <param argument="alpha" type="float" value="" optional="True" label="Alpha" help="The highest p-value for features to be kept."/>
983 </section> 1070 </section>
984 </when> 1071 </when>
985 <when value="SelectFdr"> 1072 <when value="SelectFdr">
986 <expand macro="feature_selection_score_function" /> 1073 <expand macro="feature_selection_score_function" />
987 <section name="options" title="Other Options" expanded="True"> 1074 <section name="options" title="Advanced Options" expanded="False">
988 <param argument="alpha" type="float" value="" optional="True" label="Alpha" help="The highest uncorrected p-value for features to keep."/> 1075 <param argument="alpha" type="float" value="" optional="True" label="Alpha" help="The highest uncorrected p-value for features to keep."/>
989 </section> 1076 </section>
990 </when> 1077 </when>
991 <when value="SelectFwe"> 1078 <when value="SelectFwe">
992 <expand macro="feature_selection_score_function" /> 1079 <expand macro="feature_selection_score_function" />
993 <section name="options" title="Other Options" expanded="True"> 1080 <section name="options" title="Advanced Options" expanded="False">
994 <param argument="alpha" type="float" value="" optional="True" label="Alpha" help="The highest uncorrected p-value for features to keep."/> 1081 <param argument="alpha" type="float" value="" optional="True" label="Alpha" help="The highest uncorrected p-value for features to keep."/>
995 </section> 1082 </section>
996 </when> 1083 </when>
997 <when value="RFE"> 1084 <when value="RFE">
998 <expand macro="feature_selection_estimator" /> 1085 <expand macro="estimator_selector_all"/>
999 <conditional name="extra_estimator"> 1086 <section name="options" title="Advanced Options" expanded="False">
1000 <expand macro="feature_selection_extra_estimator" />
1001 <expand macro="feature_selection_estimator_choices" />
1002 </conditional>
1003 <section name="options" title="Other Options" expanded="True">
1004 <param argument="n_features_to_select" type="integer" value="" optional="true" label="n_features_to_select" help="The number of features to select. If None, half of the features are selected." /> 1087 <param argument="n_features_to_select" type="integer" value="" optional="true" label="n_features_to_select" help="The number of features to select. If None, half of the features are selected." />
1005 <param argument="step" type="float" value="1" label="step" optional="true" help="Default = 1. " /> 1088 <param argument="step" type="float" value="1" label="step" optional="true" help="Default = 1. " />
1006 <param argument="verbose" type="integer" value="0" label="verbose" help="Controls verbosity of output." /> 1089 <param argument="verbose" type="integer" value="0" label="verbose" help="Controls verbosity of output." />
1007 </section> 1090 </section>
1008 </when> 1091 </when>
1009 <when value="RFECV"> 1092 <when value="RFECV">
1010 <expand macro="feature_selection_estimator" /> 1093 <expand macro="estimator_selector_all"/>
1011 <conditional name="extra_estimator"> 1094 <section name="options" title="Advanced Options" expanded="False">
1012 <expand macro="feature_selection_extra_estimator" />
1013 <expand macro="feature_selection_estimator_choices" />
1014 </conditional>
1015 <section name="options" title="Other Options" expanded="True">
1016 <param argument="step" type="float" value="1" label="step" optional="true" help="Default = 1. " /> 1095 <param argument="step" type="float" value="1" label="step" optional="true" help="Default = 1. " />
1017 <param argument="cv" type="integer" value="" optional="true" label="cv" help="Determines the cross-validation splitting strategy" /> 1096 <param argument="cv" type="integer" value="" optional="true" label="cv" help="Determines the cross-validation splitting strategy" />
1018 <param argument="scoring" type="text" value="" optional="true" label="scoring" help="A string (see model evaluation documentation) or a scorer callable object / function with signature scorer(estimator, X, y)."/> 1097 <param argument="scoring" type="text" value="" optional="true" label="scoring" help="A string (see model evaluation documentation) or a scorer callable object / function with signature scorer(estimator, X, y)."/>
1019 <param argument="verbose" type="integer" value="0" label="verbose" help="Controls verbosity of output." /> 1098 <param argument="verbose" type="integer" value="0" label="verbose" help="Controls verbosity of output." />
1020 <param argument="n_jobs" type="integer" value="1" label="n_jobs" help="Number of cores to run in parallel while fitting across folds. Defaults to 1 core."/> 1099 <param argument="n_jobs" type="integer" value="1" label="n_jobs" help="Number of cores to run in parallel while fitting across folds. Defaults to 1 core."/>
1021 </section> 1100 </section>
1022 </when> 1101 </when>
1023 <when value="VarianceThreshold"> 1102 <when value="VarianceThreshold">
1024 <section name="options" title="Options" expanded="True"> 1103 <section name="options" title="Options" expanded="False">
1025 <param argument="threshold" type="float" value="" optional="True" label="Threshold" help="Features with a training-set variance lower than this threshold will be removed."/> 1104 <param argument="threshold" type="float" value="" optional="True" label="Threshold" help="Features with a training-set variance lower than this threshold will be removed."/>
1026 </section> 1105 </section>
1027 </when> 1106 </when>
1028 <!--when value="chi2"> 1107 <!--when value="chi2">
1029 </when> 1108 </when>
1046 <option value="mutual_info_classif">mutual_info_classif - Estimate mutual information for a discrete target variable</option> 1125 <option value="mutual_info_classif">mutual_info_classif - Estimate mutual information for a discrete target variable</option>
1047 <option value="mutual_info_regression">mutual_info_regression - Estimate mutual information for a continuous target variable</option> 1126 <option value="mutual_info_regression">mutual_info_regression - Estimate mutual information for a continuous target variable</option>
1048 </param> 1127 </param>
1049 </xml> 1128 </xml>
1050 1129
1051 <xml name="feature_selection_estimator"> 1130 <xml name="feature_selection_output_mothods">
1052 <param argument="estimator" type="select" label="Select an estimator" help="The base estimator from which the transformer is built."> 1131 <conditional name="output_method_selector">
1053 <option value="svm.SVR(kernel=&quot;linear&quot;)">svm.SVR(kernel=&quot;linear&quot;)</option> 1132 <param name="selected_method" type="select" label="Select an output method:">
1054 <option value="svm.SVC(kernel=&quot;linear&quot;)">svm.SVC(kernel=&quot;linear&quot;)</option>
1055 <option value="svm.LinearSVC(penalty=&quot;l1&quot;, dual=False, tol=1e-3)">svm.LinearSVC(penalty=&quot;l1&quot;, dual=False, tol=1e-3)</option>
1056 <option value="linear_model.LassoCV()">linear_model.LassoCV()</option>
1057 <option value="ensemble.RandomForestRegressor(n_estimators = 1000, random_state = 42)">ensemble.RandomForestRegressor(n_estimators = 1000, random_state = 42)</option>
1058 </param>
1059 </xml>
1060
1061 <xml name="feature_selection_extra_estimator">
1062 <param name="has_estimator" type="select" label="Does your estimator on the list above?">
1063 <option value="yes">Yes, my estimator is on the list</option>
1064 <option value="no">No, I need make a new estimator</option>
1065 <yield/>
1066 </param>
1067 </xml>
1068
1069 <xml name="feature_selection_estimator_choices">
1070 <when value="yes">
1071 </when>
1072 <when value="no">
1073 <param name="new_estimator" type="text" value="" label="Make a new estimator" />
1074 </when>
1075 <yield/>
1076 </xml>
1077
1078 <xml name="feature_selection_methods">
1079 <conditional name="select_methods">
1080 <param name="selected_method" type="select" label="Select an operation">
1081 <option value="fit_transform">fit_transform - Fit to data, then transform it</option> 1133 <option value="fit_transform">fit_transform - Fit to data, then transform it</option>
1082 <option value="get_support">get_support - Get a mask, or integer index, of the features selected</option> 1134 <option value="get_support">get_support - Get a mask, or integer index, of the features selected</option>
1083 </param> 1135 </param>
1084 <when value="fit_transform"> 1136 <when value="fit_transform">
1085 <!--**fit_params--> 1137 <!--**fit_params-->
1099 1151
1100 <xml name="scoring"> 1152 <xml name="scoring">
1101 <param argument="scoring" type="text" value="" optional="true" label="scoring" help="A metric used to evaluate the estimator"/> 1153 <param argument="scoring" type="text" value="" optional="true" label="scoring" help="A metric used to evaluate the estimator"/>
1102 </xml> 1154 </xml>
1103 1155
1104 <xml name="pre_dispatch" token_type="text" token_default_value="all" token_help="Number of predispatched jobs for parallel execution"> 1156 <xml name="pre_dispatch" token_type="hidden" token_default_value="all" token_help="Number of predispatched jobs for parallel execution">
1105 <param argument="pre_dispatch" type="@TYPE@" value="@DEFAULT_VALUE@" optional="true" label="pre_dispatch" help="@HELP@"/> 1157 <param argument="pre_dispatch" type="@TYPE@" value="@DEFAULT_VALUE@" optional="true" label="pre_dispatch" help="@HELP@"/>
1106 </xml> 1158 </xml>
1107 1159
1160 <xml name="search_cv_estimator">
1161 <param name="infile_pipeline" type="data" format="zip" label="Choose the dataset containing pipeline object:"/>
1162 <section name="search_params_builder" title="Search parameters Builder" expanded="true">
1163 <repeat name="param_set" min="1" max="20" title="Parameter setting for search:">
1164 <conditional name="search_param_selector">
1165 <param name="selected_param_type" type="select" label="Choose the transformation the parameter belongs to">
1166 <option value="final_estimator_p" selected="true">Final estimator</option>
1167 <option value="prep_1_p">Pre-processing step #1</option>
1168 <option value="prep_2_p">Pre-processing step #2</option>
1169 <option value="prep_3_p">Pre-processing step #3</option>
1170 <option value="prep_4_p">Pre-processing step #4</option>
1171 <option value="prep_5_p">Pre-processing step #5</option>
1172 </param>
1173 <when value="final_estimator_p">
1174 <expand macro="search_param_input" />
1175 </when>
1176 <when value="prep_1_p">
1177 <expand macro="search_param_input" label="Pre_processing component #1 parameter:" help="One parameter per box. For example: with_centering: [True, False]."/>
1178 </when>
1179 <when value="prep_2_p">
1180 <expand macro="search_param_input" label="Pre_processing component #2 parameter:" help="One parameter per box. For example: k: [3, 5, 7, 9]. See bottom for more examples"/>
1181 </when>
1182 <when value="prep_3_p">
1183 <expand macro="search_param_input" label="Pre_processing component #3 parameter:" help="One parameter per box. For example: n_components: [1, 10, 100, 1000]. See bottom for more examples"/>
1184 </when>
1185 <when value="prep_4_p">
1186 <expand macro="search_param_input" label="Pre_processing component #4 parameter:" help="One parameter per box. For example: n_components: [1, 10, 100, 1000]. See bottom for more examples"/>
1187 </when>
1188 <when value="prep_5_p">
1189 <expand macro="search_param_input" label="Pre_processing component #5 parameter:" help="One parameter per box. For example: affinity: ['euclidean', 'l1', 'l2', 'manhattan']. See bottom for more examples"/>
1190 </when>
1191 </conditional>
1192 </repeat>
1193 </section>
1194 </xml>
1195
1196 <xml name="search_param_input" token_label="Estimator parameter:" token_help="One parameter per box. For example: C: [1, 10, 100, 1000]. See bottom for more examples">
1197 <param name="search_p" type="text" value="" size="100" optional="true" label="@LABEL@" help="@HELP@">
1198 <sanitizer>
1199 <valid initial="default">
1200 <add value="&apos;"/>
1201 <add value="&quot;"/>
1202 <add value="["/>
1203 <add value="]"/>
1204 </valid>
1205 </sanitizer>
1206 </param>
1207 </xml>
1208
1209 <xml name="search_cv_options">
1210 <expand macro="scoring"/>
1211 <expand macro="model_validation_common_options"/>
1212 <expand macro="pre_dispatch" value="2*n_jobs" help="Controls the number of jobs that get dispatched during parallel execution"/>
1213 <param argument="iid" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" label="iid" help="If True, data is identically distributed across the folds"/>
1214 <param argument="refit" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" label="refit" help="Refit an estimator using the best found parameters on the whole dataset."/>
1215 <!--error_score-->
1216 <param argument="return_train_score" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="return_train_score" help=""/>
1217 </xml>
1218
1219 <xml name="estimator_selector_all">
1220 <conditional name="estimator_selector">
1221 <param name="selected_module" type="select" label="Choose the module that contains target estimator:" >
1222 <option value="svm" selected="true">sklearn.svm</option>
1223 <option value="linear_model">sklearn.linear_model</option>
1224 <option value="ensemble">sklearn.ensemble</option>
1225 <option value="naive_bayes">sklearn.naive_bayes</option>
1226 <option value="tree">sklearn.tree</option>
1227 <option value="neighbors">sklearn.neighbors</option>
1228 <option value="xgboost">xgboost</option>
1229 <!--more-->
1230 </param>
1231 <when value="svm">
1232 <param name="selected_estimator" type="select" label="Choose estimator class:">
1233 <option value="LinearSVC" selected="true">LinearSVC</option>
1234 <option value="LinearSVR">LinearSVR</option>
1235 <option value="NuSVC">NuSVC</option>
1236 <option value="NuSVR">NuSVR</option>
1237 <option value="OneClassSVM">OneClassSVM</option>
1238 <option value="SVC">SVC</option>
1239 <option value="SVR">SVR</option>
1240 </param>
1241 <expand macro="estimator_params_text"/>
1242 </when>
1243 <when value="linear_model">
1244 <param name="selected_estimator" type="select" label="Choose estimator class:">
1245 <option value="ARDRegression" selected="true">ARDRegression</option>
1246 <option value="BayesianRidge">BayesianRidge</option>
1247 <option value="ElasticNet">ElasticNet</option>
1248 <option value="ElasticNetCV">ElasticNetCV</option>
1249 <option value="HuberRegressor">HuberRegressor</option>
1250 <option value="Lars">Lars</option>
1251 <option value="LarsCV">LarsCV</option>
1252 <option value="Lasso">Lasso</option>
1253 <option value="LassoCV">LassoCV</option>
1254 <option value="LassoLars">LassoLars</option>
1255 <option value="LassoLarsCV">LassoLarsCV</option>
1256 <option value="LassoLarsIC">LassoLarsIC</option>
1257 <option value="LinearRegression">LinearRegression</option>
1258 <option value="LogisticRegression">LogisticRegression</option>
1259 <option value="LogisticRegressionCV">LogisticRegressionCV</option>
1260 <option value="MultiTaskLasso">MultiTaskLasso</option>
1261 <option value="MultiTaskElasticNet">MultiTaskElasticNet</option>
1262 <option value="MultiTaskLassoCV">MultiTaskLassoCV</option>
1263 <option value="MultiTaskElasticNetCV">MultiTaskElasticNetCV</option>
1264 <option value="OrthogonalMatchingPursuit">OrthogonalMatchingPursuit</option>
1265 <option value="OrthogonalMatchingPursuitCV">OrthogonalMatchingPursuitCV</option>
1266 <option value="PassiveAggressiveClassifier">PassiveAggressiveClassifier</option>
1267 <option value="PassiveAggressiveRegressor">PassiveAggressiveRegressor</option>
1268 <option value="Perceptron">Perceptron</option>
1269 <option value="RANSACRegressor">RANSACRegressor</option>
1270 <option value="Ridge">Ridge</option>
1271 <option value="RidgeClassifier">RidgeClassifier</option>
1272 <option value="RidgeClassifierCV">RidgeClassifierCV</option>
1273 <option value="RidgeCV">RidgeCV</option>
1274 <option value="SGDClassifier">SGDClassifier</option>
1275 <option value="SGDRegressor">SGDRegressor</option>
1276 <option value="TheilSenRegressor">TheilSenRegressor</option>
1277 </param>
1278 <expand macro="estimator_params_text"/>
1279 </when>
1280 <when value="ensemble">
1281 <param name="selected_estimator" type="select" label="Choose estimator class:">
1282 <option value="AdaBoostClassifier" selected="true">AdaBoostClassifier</option>
1283 <option value="AdaBoostRegressor">AdaBoostRegressor</option>
1284 <option value="BaggingClassifier">BaggingClassifier</option>
1285 <option value="BaggingRegressor">BaggingRegressor</option>
1286 <option value="ExtraTreesClassifier">ExtraTreesClassifier</option>
1287 <option value="ExtraTreesRegressor">ExtraTreesRegressor</option>
1288 <option value="GradientBoostingClassifier">GradientBoostingClassifier</option>
1289 <option value="GradientBoostingRegressor">GradientBoostingRegressor</option>
1290 <option value="IsolationForest">IsolationForest</option>
1291 <option value="RandomForestClassifier">RandomForestClassifier</option>
1292 <option value="RandomForestRegressor">RandomForestRegressor</option>
1293 <option value="RandomTreesEmbedding">RandomTreesEmbedding</option>
1294 <option value="VotingClassifier">VotingClassifier</option>
1295 </param>
1296 <expand macro="estimator_params_text"/>
1297 </when>
1298 <when value="naive_bayes">
1299 <param name="selected_estimator" type="select" label="Choose estimator class:">
1300 <option value="BernoulliNB" selected="true">BernoulliNB</option>
1301 <option value="GaussianNB">GaussianNB</option>
1302 <option value="MultinomialNB">MultinomialNB</option>
1303 </param>
1304 <expand macro="estimator_params_text"/>
1305 </when>
1306 <when value="tree">
1307 <param name="selected_estimator" type="select" label="Choose estimator class:">
1308 <option value="DecisionTreeClassifier" selected="true">DecisionTreeClassifier</option>
1309 <option value="DecisionTreeRegressor">DecisionTreeRegressor</option>
1310 <option value="ExtraTreeClassifier">ExtraTreeClassifier</option>
1311 <option value="ExtraTreeRegressor">ExtraTreeRegressor</option>
1312 </param>
1313 <expand macro="estimator_params_text"/>
1314 </when>
1315 <when value="neighbors">
1316 <param name="selected_estimator" type="select" label="Choose estimator class:">
1317 <option value="BallTree" selected="true">BallTree</option>
1318 <option value="DistanceMetric">DistanceMetric</option>
1319 <option value="KDTree">KDTree</option>
1320 <option value="KernelDensity">KernelDensity</option>
1321 <option value="KNeighborsClassifier">KNeighborsClassifier</option>
1322 <option value="KNeighborsRegressor">KNeighborsRegressor</option>
1323 <option value="LocalOutlierFactor">LocalOutlierFactor</option>
1324 <option value="RadiusNeighborsClassifier">RadiusNeighborsClassifier</option>
1325 <option value="RadiusNeighborsRegressor">RadiusNeighborsRegressor</option>
1326 <option value="NearestCentroid">NearestCentroid</option>
1327 <option value="NearestNeighbors">NearestNeighbors</option>
1328 </param>
1329 <expand macro="estimator_params_text"/>
1330 </when>
1331 <when value="xgboost">
1332 <param name="selected_estimator" type="select" label="Choose estimator class:">
1333 <option value="XGBRegressor" selected="true">XGBRegressor</option>
1334 <option value="XGBClassifier">XGBClassifier</option>
1335 </param>
1336 <expand macro="estimator_params_text"/>
1337 </when>
1338 </conditional>
1339 </xml>
1340
1341 <xml name="estimator_params_text" token_label="Type in estimator parameters:"
1342 token_help="Parameters in dictionary without braces ('{}'), e.g., 'C': 1, 'kernel': 'linear'. No double quotes. Leave this box blank for default estimator.">
1343 <param name="text_params" type="text" value="" size="50" optional="true" label="@LABEL@" help="@HELP@">
1344 <sanitizer>
1345 <valid initial="default">
1346 <add value="&apos;"/>
1347 </valid>
1348 </sanitizer>
1349 </param>
1350 </xml>
1351
1352 <xml name="kernel_approximation_all">
1353 <conditional name="kernel_approximation_selector">
1354 <param name="select_algorithm" type="select" label="Choose a kernel approximation algorithm:">
1355 <option value="Nystroem" selected="true">Nystroem</option>
1356 <option value="RBFSampler">RBFSampler</option>
1357 <option value="AdditiveChi2Sampler">AdditiveChi2Sampler</option>
1358 <option value="SkewedChi2Sampler">SkewedChi2Sampler</option>
1359 </param>
1360 <when value="Nystroem">
1361 <expand macro="estimator_params_text" label="Type in kernel approximater parameters:"
1362 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'kernel': 'rbf'. No double quotes. Leave this box blank for class default."/>
1363 </when>
1364 <when value="RBFSampler">
1365 <expand macro="estimator_params_text" label="Type in kernel approximater parameters:"
1366 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'gamma': 1.0. No double quotes. Leave this box blank for class default."/>
1367 </when>
1368 <when value="AdditiveChi2Sampler">
1369 <expand macro="estimator_params_text" label="Type in kernel approximater parameters:"
1370 help="Parameters in dictionary without braces ('{}'), e.g., 'sample_steps': 2, 'sample_interval': None. No double quotes. Leave this box blank for class default."/>
1371 </when>
1372 <when value="SkewedChi2Sampler">
1373 <expand macro="estimator_params_text" label="Type in kernel approximater parameters:"
1374 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'skewedness': 1.0. No double quotes. Leave this box blank for class default."/>
1375 </when>
1376 </conditional>
1377 </xml>
1378
1379 <xml name="matrix_decomposition_all">
1380 <conditional name="matrix_decomposition_selector">
1381 <param name="select_algorithm" type="select" label="Choose a matrix decomposition algorithm:">
1382 <option value="DictionaryLearning" selected="true">DictionaryLearning</option>
1383 <option value="FactorAnalysis">FactorAnalysis</option>
1384 <option value="FastICA">FastICA</option>
1385 <option value="IncrementalPCA">IncrementalPCA</option>
1386 <option value="KernelPCA">KernelPCA</option>
1387 <option value="LatentDirichletAllocation">LatentDirichletAllocation</option>
1388 <option value="MiniBatchDictionaryLearning">MiniBatchDictionaryLearning</option>
1389 <option value="MiniBatchSparsePCA">MiniBatchSparsePCA</option>
1390 <option value="NMF">NMF</option>
1391 <option value="PCA">PCA</option>
1392 <option value="SparsePCA">SparsePCA</option>
1393 <option value="SparseCoder">SparseCoder</option>
1394 <option value="TruncatedSVD">TruncatedSVD</option>
1395 </param>
1396 <when value="DictionaryLearning">
1397 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1398 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': None, 'alpha': 1.0. No double quotes. Leave this box blank for class default."/>
1399 </when>
1400 <when value="FactorAnalysis">
1401 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1402 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'random_state': 42. No double quotes. Leave this box blank for class default."/>
1403 </when>
1404 <when value="FastICA">
1405 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1406 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'random_state': 42. No double quotes. Leave this box blank for class default."/>
1407 </when>
1408 <when value="IncrementalPCA">
1409 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1410 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'whiten': False. No double quotes. Leave this box blank for class default."/>
1411 </when>
1412 <when value="KernelPCA">
1413 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1414 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'random_state': 42. No double quotes. Leave this box blank for class default."/>
1415 </when>
1416 <when value="LatentDirichletAllocation">
1417 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1418 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'random_state': 42. No double quotes. Leave this box blank for class default."/>
1419 </when>
1420 <when value="MiniBatchDictionaryLearning">
1421 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1422 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'random_state': 42. No double quotes. Leave this box blank for class default."/>
1423 </when>
1424 <when value="MiniBatchSparsePCA">
1425 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1426 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'random_state': 42. No double quotes. Leave this box blank for class default."/>
1427 </when>
1428 <when value="NMF">
1429 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1430 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'init': 'random'. No double quotes. Leave this box blank for class default."/>
1431 </when>
1432 <when value="PCA">
1433 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1434 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'random_state': 42. No double quotes. Leave this box blank for class default."/>
1435 </when>
1436 <when value="SparsePCA">
1437 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1438 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 100, 'random_state': 42. No double quotes. Leave this box blank for class default."/>
1439 </when>
1440 <when value="SparseCoder">
1441 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1442 help="Parameters in dictionary without braces ('{}'), e.g., 'transform_algorithm': 'omp', 'transform_alpha': 1.0. No double quotes. Leave this box blank for class default."/>
1443 </when>
1444 <when value="TruncatedSVD">
1445 <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"
1446 help="Parameters in dictionary without braces ('{}'), e.g., 'n_components': 2, 'algorithm': 'randomized'. No double quotes. Leave this box blank for default estimator."/>
1447 </when>
1448 </conditional>
1449 </xml>
1450
1451 <xml name="FeatureAgglomeration">
1452 <conditional name="FeatureAgglomeration_selector">
1453 <param name="select_algorithm" type="select" label="Choose the algorithm:">
1454 <option value="FeatureAgglomeration" selected="true">FeatureAgglomeration</option>
1455 </param>
1456 <when value="FeatureAgglomeration">
1457 <expand macro="estimator_params_text" label="Type in parameters:"
1458 help="Parameters in dictionary without braces ('{}'), e.g., 'n_clusters': 2, 'affinity': 'euclidean'. No double quotes. Leave this box blank for class default."/>
1459 </when>
1460 </conditional>
1461 </xml>
1108 <!-- Outputs --> 1462 <!-- Outputs -->
1109 1463
1110 <xml name="output"> 1464 <xml name="output">
1111 <outputs> 1465 <outputs>
1112 <data format="tabular" name="outfile_predict"> 1466 <data format="tabular" name="outfile_predict">
1115 <data format="zip" name="outfile_fit"> 1469 <data format="zip" name="outfile_fit">
1116 <filter>selected_tasks['selected_task'] == 'train'</filter> 1470 <filter>selected_tasks['selected_task'] == 'train'</filter>
1117 </data> 1471 </data>
1118 </outputs> 1472 </outputs>
1119 </xml> 1473 </xml>
1120
1121 1474
1122 <!--Citations--> 1475 <!--Citations-->
1123 <xml name="eden_citation"> 1476 <xml name="eden_citation">
1124 <citations> 1477 <citations>
1125 <citation type="doi">10.5281/zenodo.15094</citation> 1478 <citation type="doi">10.5281/zenodo.15094</citation>