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H2O Algorithms
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package hex.schemas;

import hex.modelselection.ModelSelectionModel;
import water.api.API;
import water.api.schemas3.KeyV3;
import water.api.schemas3.ModelOutputSchemaV3;
import water.api.schemas3.ModelSchemaV3;

public class ModelSelectionModelV3 extends ModelSchemaV3 {
    public static final class ModelSelectionModelOutputV3 extends ModelOutputSchemaV3 {
        @API(help="Names of predictors in the best predictor subset")
        String[][] best_predictors_subset;
        
        @API(help="R2 values of all possible predictor subsets.  Only for mode='allsubsets' or 'maxr'.")

        double[] best_r2_values;  // store the best R2 values of the best models with fix number of predictors
        
        @API(help="at each predictor subset size, the predictor added is collected in this array.  Not for mode = " +
                "'backward'.")
        String[][] predictors_added_per_step;

        @API(help="at each predictor subset size, the predictor removed is collected in this array.")
        String[][] predictors_removed_per_step;

        @API(help="p-values of chosen predictor subsets at each subset size. Only for model='backward'.")
        double[][] coef_p_values;

        @API(help="z-values of chosen predictor subsets at each subset size. Only for model='backward'.")
        double[][] z_values;
        
        @API(help="Key of models containing best 1-predictor model, best 2-predictors model, ....")
        KeyV3.ModelKeyV3[] best_model_ids;
        
        @API(help="arrays of string arrays containing coefficient names of best 1-predictor model, best 2-predictors model, ....")
        String[][] coefficient_names;

        @API(help="store coefficient values for each predictor subset.  Only for maxrsweep when build_glm_model is false.")
        double[][]  coefficient_values;

        @API(help="store standardized coefficient values for each predictor subset.  Only for maxrsweep when build_glm_model is false.")
        double[][]  coefficient_values_normalized;
        
        @Override
        public ModelSelectionModelOutputV3 fillFromImpl(ModelSelectionModel.ModelSelectionModelOutput impl) {
            super.fillFromImpl(impl);   // fill in the best_model_predictors_r2 table here when done
            return this;
        }
        
    }
    public ModelSelectionV3.ModelSelectionParametersV3 createParametersSchema() { return new ModelSelectionV3.ModelSelectionParametersV3(); }
    public ModelSelectionModelOutputV3 createOutputSchema() { return new ModelSelectionModelOutputV3();}
    
    @Override
    public ModelSelectionModel createImpl() {
        ModelSelectionModel.ModelSelectionParameters parms = parameters.createImpl();
        return new ModelSelectionModel(model_id.key(), parms, null);
    }
}