comparison main_macros.xml @ 6:961e9696f3d8 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254

5:d093d6091216

            label="Use a copy of data for precomputing row normalization" help=" "/>
      </section>
    </when>
    <yield/>
  </xml>

  <!-- Outputs -->

  <xml name="output">
    <outputs>

6:961e9696f3d8

            label="Use a copy of data for precomputing row normalization" help=" "/>
      </section>
    </when>
    <yield/>
  </xml>
  <xml name="feature_selection_score_function">
    <param argument="score_func" type="select" label="Select a score function">
      <option value="chi2">chi2 - Compute chi-squared stats between each non-negative feature and class</option>
      <option value="f_classif">f_classif - Compute the ANOVA F-value for the provided sample</option>
      <option value="f_regression">f_regression - Univariate linear regression tests</option>
      <option value="mutual_info_classif">mutual_info_classif - Estimate mutual information for a discrete target variable</option>
      <option value="mutual_info_regression">mutual_info_regression - Estimate mutual information for a continuous target variable</option>
    </param>
  </xml>
  <xml name="feature_selection_estimator">
    <param argument="estimator" type="select" label="Select an estimator" help="The base estimator from which the transformer is built.">
      <option value="svm.SVR(kernel=&quot;linear&quot;)">svm.SVR(kernel=&quot;linear&quot;)</option>
      <option value="svm.SVC(kernel=&quot;linear&quot;)">svm.SVC(kernel=&quot;linear&quot;)</option>
      <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>
      <option value="linear_model.LassoCV()">linear_model.LassoCV()</option>
      <option value="ensemble.RandomForestRegressor(n_estimators = 1000, random_state = 42)">ensemble.RandomForestRegressor(n_estimators = 1000, random_state = 42)</option>
    </param>
  </xml>
  <xml name="feature_selection_extra_estimator">   
      <param name="has_estimator" type="select" label="Does your estimator on the list above?">
        <option value="yes">Yes, my estimator is on the list</option>
        <option value="no">No, I need make a new estimator</option>
        <yield/>
      </param>
  </xml>
  <xml name="feature_selection_estimator_choices">
    <when value="yes">
    </when>
    <when value="no">
      <param name="new_estimator" type="text" value="" label="Make a new estimator" />
    </when>
    <yield/>
  </xml>
  <xml name="feature_selection_methods">
    <conditional name="select_methods">
      <param name="selected_method" type="select" label="Select an operation">
          <option value="fit_transform">fit_transform - Fit to data, then transform it</option>
          <option value="get_support">get_support - Get a mask, or integer index, of the features selected</option>
      </param>
      <when value="fit_transform">
        <!--**fit_params-->
      </when>
      <when value="get_support">
        <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."/>
      </when>
    </conditional>
  </xml>

  <!-- Outputs -->

  <xml name="output">
    <outputs>