public class KMeansModel extends hex.ClusteringModel<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>
Modifier and Type | Class and Description |
---|---|
static class |
KMeansModel.KMeansOutput |
static class |
KMeansModel.KMeansParameters |
hex.ClusteringModel.ClusteringOutput, hex.ClusteringModel.ClusteringParameters
Constructor and Description |
---|
KMeansModel(water.Key selfKey,
KMeansModel.KMeansParameters parms,
KMeansModel.KMeansOutput output) |
Modifier and Type | Method and Description |
---|---|
hex.ModelMetrics.MetricBuilder |
makeMetricBuilder(java.lang.String[] domain) |
protected double[] |
score0(double[] data,
double[] preds) |
protected boolean |
toJavaCheckTooBig() |
protected void |
toJavaPredictBody(water.util.SB bodySb,
water.util.SB classCtxSb,
water.util.SB fileCtxSb) |
adaptTestForTrain, adaptTestForTrain, addMetrics, addWarning, checksum_impl, cleanup_adapt, defaultThreshold, getPublishedKeys, isSupervised, remove_impl, score, score, score, score0, score0, score0, scoreImpl, testJavaScoring, toJava, toJava, toJavaInit, toJavaNCLASSES, toJavaPROB, toJavaSuper
delete_and_lock, delete, delete, delete, read_lock, read_lock, unlock_all, unlock, update, write_lock
checksum, getBinarySerializer, remove, remove, remove, remove
public KMeansModel(water.Key selfKey, KMeansModel.KMeansParameters parms, KMeansModel.KMeansOutput output)
public hex.ModelMetrics.MetricBuilder makeMetricBuilder(java.lang.String[] domain)
makeMetricBuilder
in class hex.Model<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>
protected double[] score0(double[] data, double[] preds)
score0
in class hex.Model<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>
protected void toJavaPredictBody(water.util.SB bodySb, water.util.SB classCtxSb, water.util.SB fileCtxSb)
toJavaPredictBody
in class hex.Model<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>
protected boolean toJavaCheckTooBig()
toJavaCheckTooBig
in class hex.Model<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>