hex.schemas.GBMV3 Maven / Gradle / Ivy

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package hex.schemas;

import hex.Distribution;
import hex.tree.gbm.GBM;
import hex.tree.gbm.GBMModel.GBMParameters;
import water.api.API;


public class GBMV3 extends SharedTreeV3 {

  public static final class GBMParametersV3 extends SharedTreeV3.SharedTreeParametersV3 {
    static public String[] fields = new String[] {
				"model_id",
				"training_frame",
				"validation_frame",
        "nfolds",
        "keep_cross_validation_predictions",
        "score_each_iteration",
        "fold_assignment",
        "fold_column",
				"response_column",
				"ignored_columns",
				"ignore_const_cols",
				"offset_column",
				"weights_column",
				"balance_classes",
				"class_sampling_factors",
				"max_after_balance_size",
				"max_confusion_matrix_size",
				"max_hit_ratio_k",
				"ntrees",
				"max_depth",
				"min_rows",
				"nbins",
        "nbins_top_level",
				"nbins_cats",
				"r2_stopping",
        "stopping_rounds",
        "stopping_metric",
        "stopping_tolerance",
				"seed",
				"build_tree_one_node",
        "learn_rate",
        "distribution",
        "tweedie_power",
        "checkpoint",
        "sample_rate",
        "col_sample_rate",
    };

    // Input fields
    @API(help="Learning rate (from 0.0 to 1.0)", gridable = true)
    public float learn_rate;

    @API(help = "Distribution function", values = { "AUTO", "bernoulli", "multinomial", "gaussian", "poisson", "gamma", "tweedie" }, gridable = true)
    public Distribution.Family distribution;

    @API(help = "Tweedie Power (between 1 and 2)", level = API.Level.secondary, gridable = true)
    public double tweedie_power;

    @API(help="Column sample rate (from 0.0 to 1.0)", gridable = true)
    public float col_sample_rate;
  }
}