hex
Class KMeans2.KMeans2Model

java.lang.Object
  water.Iced
      water.Model
          hex.KMeans2.KMeans2Model

All Implemented Interfaces:

java.lang.Cloneable, Freezable, Job.Progress

Enclosing class:

KMeans2

public static class KMeans2.KMeans2Model
extends Model
implements Job.Progress

Nested Class Summary

Nested classes/interfaces inherited from class water.Model

Model.SB

Field Summary

double[][]	clusters
double	error
int	iterations
int	max_iter
boolean	normalized

Fields inherited from class water.Model

_dataKey, _domains, _names, _selfKey, DOC_FIELDS

Constructor Summary

KMeans2.KMeans2Model(Key selfKey, Key dataKey, Frame fr)

Method Summary

float	progress()
protected float[]	score0(Chunk[] chunks, int rowInChunk, double[] tmp, float[] preds) Bulk scoring API for one row.
protected float[]	score0(double[] data, float[] preds) Subclasses implement the scoring logic.

Methods inherited from class water.Model

adapt, classNames, cm, delete, getDomainMapping, isClassifier, nclasses, responseName, score, score, score, score, score, testJavaScoring, toJava, toJavaInit, toJavaInit, toJavaPredictBody

Methods inherited from class water.Iced

clone, frozenType, init, newInstance, read, toDocField, write, writeJSON, writeJSONFields

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

clusters

public double[][] clusters

error

public double error

normalized

public boolean normalized

max_iter

public int max_iter

iterations

public int iterations

Constructor Detail

KMeans2.KMeans2Model

public KMeans2.KMeans2Model(Key selfKey,
                            Key dataKey,
                            Frame fr)

Method Detail

progress

public float progress()

Specified by:

progress in interface Job.Progress

score0

protected float[] score0(Chunk[] chunks,
                         int rowInChunk,
                         double[] tmp,
                         float[] preds)

Description copied from class: Model

Bulk scoring API for one row. Chunks are all compatible with the model, and expect the last Chunks are for the final distribution & prediction. Default method is to just load the data into the tmp array, then call subclass scoring logic.

Overrides:

score0 in class Model

score0

protected float[] score0(double[] data,
                         float[] preds)

Description copied from class: Model

Subclasses implement the scoring logic. The data is pre-loaded into a re-used temp array, in the order the model expects. The predictions are loaded into the re-used temp array, which is also returned.

Specified by:

score0 in class Model