Mercurial > repos > bgruening > sklearn_pairwise_metrics
changeset 9:efdf8df169a1 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 35fa73d6e9ba8f0789ddfb743d893d950a68af02
| author | bgruening |
|---|---|
| date | Tue, 10 Apr 2018 15:14:23 -0400 |
| parents | 36cf36c4a75c |
| children | d39bac038704 |
| files | main_macros.xml test-data/gbc_model01 test-data/gbc_result01 test-data/gbr_model01 test-data/gbr_prediction_result01.tabular test-data/regression_X.tabular test-data/regression_test_X.tabular test-data/regression_y.tabular |
| diffstat | 8 files changed, 760 insertions(+), 6 deletions(-) [+] |
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--- a/main_macros.xml Thu Mar 22 13:42:19 2018 -0400 +++ b/main_macros.xml Tue Apr 10 15:14:23 2018 -0400 @@ -66,6 +66,7 @@ <when value="load"> <param name="infile_model" type="data" format="@MODEL@" label="Models" help="Select a model file."/> <param name="infile_data" type="data" format="@DATA@" label="Data (tabular)" help="Select the dataset you want to classify."/> + <param name="header" type="boolean" optional="True" truevalue="booltrue" falsevalue="boolfalse" checked="False" label="Does the dataset contain header:" /> <conditional name="prediction_options"> <param name="prediction_option" type="select" label="Select the type of prediction"> <option value="predict">Predict class labels</option> @@ -174,12 +175,12 @@ <param argument="max_depth" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Maximum depth of the tree" help="@HELP@"/> </xml> - <xml name="min_samples_split" token_default_value="2" token_help=" "> - <param argument="min_samples_split" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Minimum number of samples required to split an internal node" help="@HELP@"/> + <xml name="min_samples_split" token_type="integer" token_default_value="2" token_help=" "> + <param argument="min_samples_split" type="@TYPE@" optional="true" value="@DEFAULT_VALUE@" label="Minimum number of samples required to split an internal node" help="@HELP@"/> </xml> - <xml name="min_samples_leaf" token_default_value="1" token_help=" "> - <param argument="min_samples_leaf" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Minimum number of samples in newly created leaves" help="@HELP@"/> + <xml name="min_samples_leaf" token_type="integer" token_default_value="1" token_label="Minimum number of samples in newly created leaves" token_help=" "> + <param argument="min_samples_leaf" type="@TYPE@" optional="true" value="@DEFAULT_VALUE@" label="@LABEL@" help="@HELP@"/> </xml> <xml name="min_weight_fraction_leaf" token_default_value="0.0" token_help=" "> @@ -190,6 +191,10 @@ <param argument="max_leaf_nodes" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Maximum number of leaf nodes in best-first method" help="@HELP@"/> </xml> + <xml name="min_impurity_decrease" token_default_value="0" token_help=" "> + <param argument="min_impurity_decrease" type="float" value="@DEFAULT_VALUE@" optional="true" label="The threshold value of impurity for stopping node splitting" help="@HELP@"/> + </xml> + <xml name="bootstrap" token_checked="true" token_help=" "> <param argument="bootstrap" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="@CHECKED@" label="Use bootstrap samples for building trees." help="@HELP@"/> </xml> @@ -202,18 +207,57 @@ </param> </xml> + <xml name="criterion2" token_help=""> + <param argument="criterion" type="select" label="Function to measure the quality of a split" > + <option value="mse">mse - mean squared error</option> + <option value="mae">mae - mean absolute error</option> + <yield/> + </param> + </xml> + <xml name="oob_score" token_checked="false" token_help=" "> <param argument="oob_score" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="@CHECKED@" label="Use out-of-bag samples to estimate the generalization error" help="@HELP@"/> </xml> - <xml name="max_features" token_default_value="auto" token_help="This could be an integer, float, string, or None. For more information please refer to help. "> - <param argument="max_features" type="text" optional="true" value="@DEFAULT_VALUE@" label="Number of features for finding the best split" help="@HELP@"/> + <xml name="max_features"> + <conditional name="select_max_features"> + <param argument="max_features" type="select" label="max_features"> + <option value="auto" selected="true">auto - max_features=n_features</option> + <option value="sqrt">sqrt - max_features=sqrt(n_features)</option> + <option value="log2">log2 - max_features=log2(n_features)</option> + <option value="number_input">I want to type the number in or input None type</option> + </param> + <when value="auto"> + </when> + <when value="sqrt"> + </when> + <when value="log2"> + </when> + <when value="number_input"> + <param name="num_max_features" type="float" value="" optional="true" label="Input max_features number:" help="If int, consider the number of features at each split; If float, then max_features is a percentage and int(max_features * n_features) features are considered at each split."/> + </when> + </conditional> + </xml> + + <xml name="verbose" token_default_value="0" token_help="If 1 then it prints progress and performance once in a while. If greater than 1 then it prints progress and performance for every tree."> + <param argument="verbose" type="integer" value="@DEFAULT_VALUE@" optional="true" label="Enable verbose output" help="@HELP@"/> </xml> <xml name="learning_rate" token_default_value="1.0" token_help=" "> <param argument="learning_rate" type="float" optional="true" value="@DEFAULT_VALUE@" label="Learning rate" help="@HELP@"/> </xml> + <xml name="subsample" token_help=" "> + <param argument="subsample" type="float" value="1.0" optional="true" label="The fraction of samples to be used for fitting the individual base learners" help="@HELP@"/> + </xml> + + <xml name="presort"> + <param argument="presort" type="select" label="Whether to presort the data to speed up the finding of best splits in fitting" > + <option value="auto" selected="true">auto</option> + <option value="true">true</option> + <option value="false">false</option> + </param> + </xml> <!--Parameters--> <xml name="tol" token_default_value="0.0" token_help_text="Early stopping heuristics based on the relative center changes. Set to default (0.0) to disable this convergence detection."> @@ -228,6 +272,10 @@ <param argument="fit_intercept" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="@CHECKED@" label="Estimate the intercept" help="If false, the data is assumed to be already centered."/> </xml> + <xml name="n_jobs" token_default_value="1" token_label="The number of jobs to run in parallel for both fit and predict"> + <param argument="n_jobs" type="integer" value="@DEFAULT_VALUE@" optional="true" label="@LABEL@" help="If -1, then the number of jobs is set to the number of cores"/> + </xml> + <xml name="n_iter" token_default_value="5" token_help_text="The number of passes over the training data (aka epochs). "> <param argument="n_iter" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Number of iterations" help="@HELP_TEXT@"/> </xml>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/gbc_result01 Tue Apr 10 15:14:23 2018 -0400 @@ -0,0 +1,6 @@ +0 1 2 3 0 +3.68258022948 2.82110345641 -3.990140724 -1.9523364774 1 +0.015942057224 -0.711958594347 0.125502976978 -0.972218263337 0 +2.08690768825 0.929399321468 -2.12924084484 -1.99714022188 1 +1.41321052084 0.523750660422 -1.4210539291 -1.49298569451 1 +0.76831404394 1.38267855169 -0.989045048734 0.649504257894 1
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