Mercurial > repos > bgruening > svm_classifier
comparison main_macros.xml @ 11:3bcc3aee938e draft
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
| author | bgruening |
|---|---|
| date | Thu, 12 Apr 2018 08:17:18 -0400 |
| parents | f54a5732d5ad |
| children | 1a89066e496b |
comparison
equal
deleted
inserted
replaced
| 10:f54a5732d5ad | 11:3bcc3aee938e |
|---|---|
| 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> |
