comparison PDAUG_ML_Models/PDAUG_ML_Models.xml @ 6:8697dc4a7f45 draft

"planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit e8c8198105af7eab636fb2405e5ff335539ca14b"

5:d5a209484c17

      </conditional>

      <conditional name='TestMethods'>
        <param name="SelTestMethods" type="select" label="Choose the Test method" argument="--TestMethod" help="Data testing method">
          <option value="Internal">Internal</option>
          <option value="TestSplit">TestSplit</option>
          <option value="External">External</option>
          <option value="Predict">Predict</option>
        </param>
        <when value="Internal">
          <param name="nFolds" type="integer" label="Cross validation" value="5" min="5" max="10" argument="--nfold" help="Cross validation"/>
        </when>
        <when value="TestSplit">

**Inputs**
    * **Training File**  Tabulalr files with labeled peptide descriptor data.  
    * **Select Machine Learning algorithms** Select algorithm. 
    * **Select Advanced Parameters** Select the advance parameter details of each of the parameters that can be found on sklearn website. 
    * **Select the test method** (predict or internal test)
    * **Cross Validation** Up to 10 fold cross-validation. 
    * **Method to Scale the data** MinMaxScaler and  standard scaler. 

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6:8697dc4a7f45

      </conditional>

      <conditional name='TestMethods'>
        <param name="SelTestMethods" type="select" label="Choose the Test method" argument="--TestMethod" help="Data testing method">
          <option value="Internal">Internal Test</option>
          <option value="TestSplit">Train Test Split</option>
          <option value="External">External Test Data</option>
          <option value="Predict">Predict Unknown</option>
        </param>
        <when value="Internal">
          <param name="nFolds" type="integer" label="Cross validation" value="5" min="5" max="10" argument="--nfold" help="Cross validation"/>
        </when>
        <when value="TestSplit">

**Inputs**
    * **Training File**  Tabulalr files with labeled peptide descriptor data.  
    * **Select Machine Learning algorithms** Select algorithm. 
    * **Select Advanced Parameters** Select the advance parameter details of each of the parameters that can be found on sklearn website. 
    * **Select the test method** (Internal Test, Train Test Split, External Test Data, and Predict Unknown)
    * **Cross Validation** Up to 10 fold cross-validation. 
    * **Method to Scale the data** MinMaxScaler and  standard scaler. 

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