hex.schemas.KMeansV3 Maven / Gradle / Ivy

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package hex.schemas;

import hex.kmeans.KMeans;
import hex.kmeans.KMeansModel.KMeansParameters;
import water.api.API;
import water.api.ClusteringModelParametersSchema;
import water.api.KeyV3;

public class KMeansV3 extends ClusteringModelBuilderSchema {

  public static final class KMeansParametersV3 extends ClusteringModelParametersSchema {
    static public String[] fields = new String[] {
        "model_id",
        "training_frame",
        "validation_frame",
        "nfolds",
        "keep_cross_validation_predictions",
        "fold_assignment",
        "fold_column",
        "ignored_columns",
        "ignore_const_cols",
        "score_each_iteration",
        "k",
        "user_points",
        "max_iterations",
        "standardize",
        "seed",
        "init"
    };

    // Input fields
    @API(help = "User-specified points", required = false)
    public KeyV3.FrameKeyV3 user_points;

    @API(help="Maximum training iterations", gridable = true)
    public int max_iterations;        // Max iterations

    @API(help = "Standardize columns", level = API.Level.secondary, gridable = true)
    public boolean standardize = true;

    @API(help = "RNG Seed", level = API.Level.expert /* tested, works: , dependsOn = {"k", "max_iterations"} */, gridable = true)
    public long seed;

    @API(help = "Initialization mode", values = { "Random", "PlusPlus", "Furthest", "User" }, gridable = true) // TODO: pull out of categorical class. . .
    public KMeans.Initialization init;
  }
}