com.google.api.services.bigquery.model

Class ClusteringMetrics

java.lang.Object

java.util.AbstractMap<String,Object>

com.google.api.client.util.GenericData

com.google.api.client.json.GenericJson

com.google.api.services.bigquery.model.ClusteringMetrics

All Implemented Interfaces:

Cloneable, Map<String,Object>

public final class ClusteringMetrics
extends com.google.api.client.json.GenericJson

Evaluation metrics for clustering models.

This is the Java data model class that specifies how to parse/serialize into the JSON that is transmitted over HTTP when working with the BigQuery API. For a detailed explanation see: https://developers.google.com/api-client-library/java/google-http-java-client/json

Author:

Google, Inc.

Nested Class Summary

Nested classes/interfaces inherited from class com.google.api.client.util.GenericData

com.google.api.client.util.GenericData.Flags

Nested classes/interfaces inherited from class java.util.AbstractMap

AbstractMap.SimpleEntry<K,V>, AbstractMap.SimpleImmutableEntry<K,V>

Nested classes/interfaces inherited from interface java.util.Map

Map.Entry<K,V>

Constructor Summary

Constructors

Constructor and Description
ClusteringMetrics()

Method Summary

Modifier and Type	Method and Description
ClusteringMetrics	clone()
List<Cluster>	getClusters() Information for all clusters.
Double	getDaviesBouldinIndex() Davies-Bouldin index.
Double	getMeanSquaredDistance() Mean of squared distances between each sample to its cluster centroid.
ClusteringMetrics	set(String fieldName, Object value)
ClusteringMetrics	setClusters(List<Cluster> clusters) Information for all clusters.
ClusteringMetrics	setDaviesBouldinIndex(Double daviesBouldinIndex) Davies-Bouldin index.
ClusteringMetrics	setMeanSquaredDistance(Double meanSquaredDistance) Mean of squared distances between each sample to its cluster centroid.

Methods inherited from class com.google.api.client.json.GenericJson

getFactory, setFactory, toPrettyString, toString

Methods inherited from class com.google.api.client.util.GenericData

entrySet, equals, get, getClassInfo, getUnknownKeys, hashCode, put, putAll, remove, setUnknownKeys

Methods inherited from class java.util.AbstractMap

clear, containsKey, containsValue, isEmpty, keySet, size, values

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.Map

compute, computeIfAbsent, computeIfPresent, forEach, getOrDefault, merge, putIfAbsent, remove, replace, replace, replaceAll

Constructor Detail

ClusteringMetrics

public ClusteringMetrics()

Method Detail

getClusters

public List<Cluster> getClusters()

Information for all clusters.

Returns:

value or null for none

setClusters

public ClusteringMetrics setClusters(List<Cluster> clusters)

Information for all clusters.

Parameters:

clusters - clusters or null for none

getDaviesBouldinIndex

public Double getDaviesBouldinIndex()

Davies-Bouldin index.

Returns:

value or null for none

setDaviesBouldinIndex

public ClusteringMetrics setDaviesBouldinIndex(Double daviesBouldinIndex)

Davies-Bouldin index.

Parameters:

daviesBouldinIndex - daviesBouldinIndex or null for none

getMeanSquaredDistance

public Double getMeanSquaredDistance()

Mean of squared distances between each sample to its cluster centroid.

Returns:

value or null for none

setMeanSquaredDistance

public ClusteringMetrics setMeanSquaredDistance(Double meanSquaredDistance)

Mean of squared distances between each sample to its cluster centroid.

Parameters:

meanSquaredDistance - meanSquaredDistance or null for none

set

public ClusteringMetrics set(String fieldName,
                             Object value)

Overrides:

set in class com.google.api.client.json.GenericJson

clone

public ClusteringMetrics clone()

Overrides:

clone in class com.google.api.client.json.GenericJson