comparison main_macros.xml @ 6:961e9696f3d8 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
author bgruening
date Thu, 12 Apr 2018 08:24:10 -0400
parents d093d6091216
children 82f51b60c4ee
comparison
equal deleted inserted replaced
5:d093d6091216 6:961e9696f3d8
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=&quot;linear&quot;)">svm.SVR(kernel=&quot;linear&quot;)</option>
802 <option value="svm.SVC(kernel=&quot;linear&quot;)">svm.SVC(kernel=&quot;linear&quot;)</option>
803 <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>
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>