hex.tree.gbm.GBMModel Maven / Gradle / Ivy
package hex.tree.gbm;
import hex.VarImp;
import hex.genmodel.GenModel;
import hex.tree.SharedTreeModel;
import water.Key;
import water.fvec.Chunk;
import water.util.SB;
public class GBMModel extends SharedTreeModel {
public static class GBMParameters extends SharedTreeModel.SharedTreeParameters {
/** Distribution functions. Note: AUTO will select gaussian for
* continuous, and multinomial for categorical response
*
* TODO: Replace with drop-down that displays different distributions
* depending on cont/cat response
*/
public enum Family { AUTO, bernoulli, multinomial, gaussian }
public Family _distribution = Family.AUTO;
public float _learn_rate=0.1f; // Learning rate from 0.0 to 1.0
}
public static class GBMOutput extends SharedTreeModel.SharedTreeOutput {
public GBMOutput( GBM b, double mse_train, double mse_valid ) { super(b,mse_train,mse_valid); }
}
public GBMModel(Key selfKey, GBMParameters parms, GBMOutput output ) { super(selfKey,parms,output); }
/** Bulk scoring API for one row. Chunks are all compatible with the model,
* and expect the last Chunks are for the final distribution and prediction.
* Default method is to just load the data into the tmp array, then call
* subclass scoring logic. */
@Override public double[] score0( Chunk chks[], int row_in_chunk, double[] tmp, double[] preds ) {
assert chks.length>=tmp.length;
for( int i=0; i