hex

Class KMeans2.KMeans2Model

java.lang.Object

water.Iced

water.Lockable<Model>

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.ModelAutobufferSerializer, Model.ModelCategory

Field Summary

Fields

Modifier and Type	Field and Description
Key	_clustersKey
double[][]	centers
static DocGen.FieldDoc[]	DOC_FIELDS
int	iterations
int	k
int	max_iter
boolean	normalized
long[]	size
double	total_within_SS
double[]	within_cluster_variances

Fields inherited from class water.Model

_dataKey, _domains, _have_cv_results, _modelClassDist, _names, _priorClassDist, GEN_BENCHMARK_CODE, training_duration_in_ms, training_start_time, warnings

Fields inherited from class water.Lockable

_key, _lockers

Constructor Summary

Constructors

Constructor and Description
KMeans2.KMeans2Model(KMeans2 params, Key selfKey, Key dataKey, java.lang.String[] names, java.lang.String[][] domains)

Method Summary

Methods

Modifier and Type	Method and Description
Futures	delete_impl(Futures fs) Remove any Model internal Keys
KMeans2	get_params()
boolean	isSupervised()
Request2	job()
double	mse() Returns mse for validation set.
int	nfeatures() Returns number of input features
float	progress()
java.lang.String	responseName()
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, adapt, addWarning, calcError, classNames, cm, errStr, getDomainMapping, getDomainMapping, getModelCategory, getModelSerializer, getUniqueId, hasCrossValModels, isClassifier, missingColumnsType, nclasses, printCrossValidationModelsHTML, score, score, score, score, score, score, scoreCrossValidation, scoreImpl, setCrossValidationError, setModelClassDistribution, start_training, start_training, stop_training, testJavaScoring, toJava, toJava, toJavaDefaultMaxIters, toJavaFillPreds0, toJavaInit, toJavaInit, toJavaNCLASSES, toJavaPredictBody, toJavaSuper, toJavaUnifyPreds, varimp

Methods inherited from class water.Lockable

delete_and_lock, delete, delete, delete, delete, is_unlocked, is_wlocked, read_lock, read_lock, unlock_all, unlock_lockable, unlock, update, write_lock

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

DOC_FIELDS

public static DocGen.FieldDoc[] DOC_FIELDS

centers

@Request.API(help="Cluster centers, always denormalized")
public double[][] centers

total_within_SS

@Request.API(help="Sum of within cluster sum of squares")
public double total_within_SS

k

@Request.API(help="Number of clusters")
public int k

size

@Request.API(help="Numbers of observations in each cluster.")
public long[] size

normalized

@Request.API(help="Whether data was normalized")
public boolean normalized

max_iter

@Request.API(help="Maximum number of iterations before stopping")
public int max_iter

iterations

@Request.API(help="Iterations the algorithm ran")
public int iterations

within_cluster_variances

@Request.API(help="Within cluster sum of squares per cluster")
public double[] within_cluster_variances

_clustersKey

@Request.API(help="The row-by-row cluster assignments")
public final Key _clustersKey

Constructor Detail

KMeans2.KMeans2Model

public KMeans2.KMeans2Model(KMeans2 params,
                    Key selfKey,
                    Key dataKey,
                    java.lang.String[] names,
                    java.lang.String[][] domains)

Method Detail

get_params

public final KMeans2 get_params()

Overrides:

get_params in class Model

job

public final Request2 job()

Overrides:

job in class Model

mse

public double mse()

Description copied from class: Model

Returns mse for validation set.

Overrides:

mse in class Model

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 and 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

nfeatures

public int nfeatures()

Description copied from class: Model

Returns number of input features

Overrides:

nfeatures in class Model

isSupervised

public boolean isSupervised()

Overrides:

isSupervised in class Model

responseName

public java.lang.String responseName()

Overrides:

responseName in class Model

delete_impl

public Futures delete_impl(Futures fs)

Remove any Model internal Keys

Overrides:

delete_impl in class Model