Mercurial > repos > bgruening > sklearn_data_preprocess
comparison main_macros.xml @ 6:9967cad18b02 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
author | bgruening |
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date | Thu, 12 Apr 2018 08:23:54 -0400 |
parents | 16ec53208a69 |
children | 3df69602db4d |
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5:16ec53208a69 | 6:9967cad18b02 |
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785 label="Use a copy of data for precomputing row normalization" help=" "/> | 785 label="Use a copy of data for precomputing row normalization" help=" "/> |
786 </section> | 786 </section> |
787 </when> | 787 </when> |
788 <yield/> | 788 <yield/> |
789 </xml> | 789 </xml> |
790 <xml name="feature_selection_score_function"> | |
791 <param argument="score_func" type="select" label="Select a score function"> | |
792 <option value="chi2">chi2 - Compute chi-squared stats between each non-negative feature and class</option> | |
793 <option value="f_classif">f_classif - Compute the ANOVA F-value for the provided sample</option> | |
794 <option value="f_regression">f_regression - Univariate linear regression tests</option> | |
795 <option value="mutual_info_classif">mutual_info_classif - Estimate mutual information for a discrete target variable</option> | |
796 <option value="mutual_info_regression">mutual_info_regression - Estimate mutual information for a continuous target variable</option> | |
797 </param> | |
798 </xml> | |
799 <xml name="feature_selection_estimator"> | |
800 <param argument="estimator" type="select" label="Select an estimator" help="The base estimator from which the transformer is built."> | |
801 <option value="svm.SVR(kernel="linear")">svm.SVR(kernel="linear")</option> | |
802 <option value="svm.SVC(kernel="linear")">svm.SVC(kernel="linear")</option> | |
803 <option value="svm.LinearSVC(penalty="l1", dual=False, tol=1e-3)">svm.LinearSVC(penalty="l1", dual=False, tol=1e-3)</option> | |
804 <option value="linear_model.LassoCV()">linear_model.LassoCV()</option> | |
805 <option value="ensemble.RandomForestRegressor(n_estimators = 1000, random_state = 42)">ensemble.RandomForestRegressor(n_estimators = 1000, random_state = 42)</option> | |
806 </param> | |
807 </xml> | |
808 <xml name="feature_selection_extra_estimator"> | |
809 <param name="has_estimator" type="select" label="Does your estimator on the list above?"> | |
810 <option value="yes">Yes, my estimator is on the list</option> | |
811 <option value="no">No, I need make a new estimator</option> | |
812 <yield/> | |
813 </param> | |
814 </xml> | |
815 <xml name="feature_selection_estimator_choices"> | |
816 <when value="yes"> | |
817 </when> | |
818 <when value="no"> | |
819 <param name="new_estimator" type="text" value="" label="Make a new estimator" /> | |
820 </when> | |
821 <yield/> | |
822 </xml> | |
823 <xml name="feature_selection_methods"> | |
824 <conditional name="select_methods"> | |
825 <param name="selected_method" type="select" label="Select an operation"> | |
826 <option value="fit_transform">fit_transform - Fit to data, then transform it</option> | |
827 <option value="get_support">get_support - Get a mask, or integer index, of the features selected</option> | |
828 </param> | |
829 <when value="fit_transform"> | |
830 <!--**fit_params--> | |
831 </when> | |
832 <when value="get_support"> | |
833 <param name="indices" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Indices" help="If True, the return value will be an array of integers, rather than a boolean mask."/> | |
834 </when> | |
835 </conditional> | |
836 </xml> | |
790 | 837 |
791 <!-- Outputs --> | 838 <!-- Outputs --> |
792 | 839 |
793 <xml name="output"> | 840 <xml name="output"> |
794 <outputs> | 841 <outputs> |