KMeans (Spark 2.3.4 JavaDoc)

Object
- org.apache.spark.ml.PipelineStage
- - org.apache.spark.ml.Estimator<KMeansModel>
  - - org.apache.spark.ml.clustering.KMeans

All Implemented Interfaces:

java.io.Serializable, Logging, Params, DefaultParamsWritable, Identifiable, MLWritable
```
public class KMeans
extends Estimator<KMeansModel>
implements DefaultParamsWritable
```
K-means clustering with support for k-means|| initialization proposed by Bahmani et al.

See Also:

Bahmani et al., Scalable k-means++., Serialized Form

Constructor Summary

Constructors
Constructor and Description

KMeans()

KMeans(String uid)

Constructors
Constructor and Description
`KMeans()`
`KMeans(String uid)`

Method Summary

All Methods Static Methods Instance Methods Abstract Methods Concrete Methods
Modifier and Type	Method and Description
`static Params`	`clear(Param<?> param)`
`KMeans`	`copy(ParamMap extra)` Creates a copy of this instance with the same UID and some extra params.
`static String`	`explainParam(Param<?> param)`
`static String`	`explainParams()`
`static ParamMap`	`extractParamMap()`
`static ParamMap`	`extractParamMap(ParamMap extra)`
`static Param<String>`	`featuresCol()`
`KMeansModel`	`fit(Dataset<?> dataset)` Fits a model to the input data.
`static <T> scala.Option<T>`	`get(Param<T> param)`
`static <T> scala.Option<T>`	`getDefault(Param<T> param)`
`static String`	`getFeaturesCol()`
`static String`	`getInitMode()`
`String`	`getInitMode()`
`static int`	`getInitSteps()`
`int`	`getInitSteps()`
`static int`	`getK()`
`int`	`getK()`
`static int`	`getMaxIter()`
`static <T> T`	`getOrDefault(Param<T> param)`
`static Param<Object>`	`getParam(String paramName)`
`static String`	`getPredictionCol()`
`static long`	`getSeed()`
`static double`	`getTol()`
`static <T> boolean`	`hasDefault(Param<T> param)`
`static boolean`	`hasParam(String paramName)`
`static Param<String>`	`initMode()`
`Param<String>`	`initMode()` Param for the initialization algorithm.
`static IntParam`	`initSteps()`
`IntParam`	`initSteps()` Param for the number of steps for the k-means\|\| initialization mode.
`static boolean`	`isDefined(Param<?> param)`
`static boolean`	`isSet(Param<?> param)`
`static IntParam`	`k()`
`IntParam`	`k()` The number of clusters to create (k).
`static KMeans`	`load(String path)`
`static IntParam`	`maxIter()`
`static Param<?>[]`	`params()`
`static Param<String>`	`predictionCol()`
`static void`	`save(String path)`
`static LongParam`	`seed()`
`static <T> Params`	`set(Param<T> param, T value)`
`KMeans`	`setFeaturesCol(String value)`
`KMeans`	`setInitMode(String value)`
`KMeans`	`setInitSteps(int value)`
`KMeans`	`setK(int value)`
`KMeans`	`setMaxIter(int value)`
`KMeans`	`setPredictionCol(String value)`
`KMeans`	`setSeed(long value)`
`KMeans`	`setTol(double value)`
`static DoubleParam`	`tol()`
`static String`	`toString()`
`StructType`	`transformSchema(StructType schema)` :: DeveloperApi ::
`String`	`uid()` An immutable unique ID for the object and its derivatives.
`StructType`	`validateAndTransformSchema(StructType schema)` Validates and transforms the input schema.
`static MLWriter`	`write()`

Methods inherited from class org.apache.spark.ml.Estimator
fit, fit, fit, fit

Methods inherited from class Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.ml.param.shared.HasMaxIter
getMaxIter, maxIter

Methods inherited from interface org.apache.spark.ml.param.shared.HasFeaturesCol
featuresCol, getFeaturesCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasSeed
getSeed, seed

Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol
getPredictionCol, predictionCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasTol
getTol, tol

Methods inherited from interface org.apache.spark.ml.param.Params
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.util.Identifiable
toString

Methods inherited from interface org.apache.spark.ml.util.DefaultParamsWritable
write

Methods inherited from interface org.apache.spark.ml.util.MLWritable
save

Methods inherited from interface org.apache.spark.internal.Logging
initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

- Constructor Detail
  - KMeans
```
public KMeans(String uid)
```
  - KMeans
```
public KMeans()
```
- Method Detail
  - load
```
public static KMeans load(String path)
```
  - toString
```
public static String toString()
```
  - params
```
public static Param<?>[] params()
```
  - explainParam
```
public static String explainParam(Param<?> param)
```
  - explainParams
```
public static String explainParams()
```
  - isSet
```
public static final boolean isSet(Param<?> param)
```
  - isDefined
```
public static final boolean isDefined(Param<?> param)
```
  - hasParam
```
public static boolean hasParam(String paramName)
```
  - getParam
```
public static Param<Object> getParam(String paramName)
```
  - set
```
public static final <T> Params set(Param<T> param,
                                   T value)
```
  - get
```
public static final <T> scala.Option<T> get(Param<T> param)
```
  - clear
```
public static final Params clear(Param<?> param)
```
  - getOrDefault
```
public static final <T> T getOrDefault(Param<T> param)
```
  - getDefault
```
public static final <T> scala.Option<T> getDefault(Param<T> param)
```
  - hasDefault
```
public static final <T> boolean hasDefault(Param<T> param)
```
  - extractParamMap
```
public static final ParamMap extractParamMap(ParamMap extra)
```
  - extractParamMap
```
public static final ParamMap extractParamMap()
```
  - maxIter
```
public static final IntParam maxIter()
```
  - getMaxIter
```
public static final int getMaxIter()
```
  - featuresCol
```
public static final Param<String> featuresCol()
```
  - getFeaturesCol
```
public static final String getFeaturesCol()
```
  - seed
```
public static final LongParam seed()
```
  - getSeed
```
public static final long getSeed()
```
  - predictionCol
```
public static final Param<String> predictionCol()
```
  - getPredictionCol
```
public static final String getPredictionCol()
```
  - tol
```
public static final DoubleParam tol()
```
  - getTol
```
public static final double getTol()
```
  - k
```
public static final IntParam k()
```
  - getK
```
public static int getK()
```
  - initMode
```
public static final Param<String> initMode()
```
  - getInitMode
```
public static String getInitMode()
```
  - initSteps
```
public static final IntParam initSteps()
```
  - getInitSteps
```
public static int getInitSteps()
```
  - save
```
public static void save(String path)
                 throws java.io.IOException
```
    Throws:
    
    java.io.IOException
  - write
```
public static MLWriter write()
```
  - uid
```
public String uid()
```
    Description copied from interface: Identifiable
    
    An immutable unique ID for the object and its derivatives.
    
    Specified by:
    
    uid in interface Identifiable
    
    Returns:
    
    (undocumented)
  - copy
```
public KMeans copy(ParamMap extra)
```
    Description copied from interface: Params
    
    Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().
    
    Specified by:
    
    copy in interface Params
    
    Specified by:
    
    copy in class Estimator<KMeansModel>
    
    Parameters:
    
    extra - (undocumented)
    
    Returns:
    
    (undocumented)
  - setFeaturesCol
```
public KMeans setFeaturesCol(String value)
```
  - setPredictionCol
```
public KMeans setPredictionCol(String value)
```
  - setK
```
public KMeans setK(int value)
```
  - setInitMode
```
public KMeans setInitMode(String value)
```
  - setInitSteps
```
public KMeans setInitSteps(int value)
```
  - setMaxIter
```
public KMeans setMaxIter(int value)
```
  - setTol
```
public KMeans setTol(double value)
```
  - setSeed
```
public KMeans setSeed(long value)
```
  - fit
```
public KMeansModel fit(Dataset<?> dataset)
```
    Description copied from class: Estimator
    
    Fits a model to the input data.
    
    Specified by:
    
    fit in class Estimator<KMeansModel>
    
    Parameters:
    
    dataset - (undocumented)
    
    Returns:
    
    (undocumented)
  - transformSchema
```
public StructType transformSchema(StructType schema)
```
    Description copied from class: PipelineStage
    
    :: DeveloperApi ::
    Check transform validity and derive the output schema from the input schema.
    We check validity for interactions between parameters during transformSchema and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by Param.validate().
    Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
    
    Specified by:
    
    transformSchema in class PipelineStage
    
    Parameters:
    
    schema - (undocumented)
    
    Returns:
    
    (undocumented)
  - k
```
public IntParam k()
```
    The number of clusters to create (k). Must be > 1. Note that it is possible for fewer than k clusters to be returned, for example, if there are fewer than k distinct points to cluster. Default: 2.
    
    Returns:
    
    (undocumented)
  - getK
```
public int getK()
```
  - initMode
```
public Param<String> initMode()
```
    Param for the initialization algorithm. This can be either "random" to choose random points as initial cluster centers, or "k-means||" to use a parallel variant of k-means++ (Bahmani et al., Scalable K-Means++, VLDB 2012). Default: k-means||.
    
    Returns:
    
    (undocumented)
  - getInitMode
```
public String getInitMode()
```
  - initSteps
```
public IntParam initSteps()
```
    Param for the number of steps for the k-means|| initialization mode. This is an advanced setting -- the default of 2 is almost always enough. Must be > 0. Default: 2.
    
    Returns:
    
    (undocumented)
  - getInitSteps
```
public int getInitSteps()
```
  - validateAndTransformSchema
```
public StructType validateAndTransformSchema(StructType schema)
```
    Validates and transforms the input schema.
    
    Parameters:
    
    schema - input schema
    
    Returns:
    
    output schema

Class KMeans

Constructor Summary

Method Summary

Methods inherited from class org.apache.spark.ml.Estimator

Methods inherited from class Object

Methods inherited from interface org.apache.spark.ml.param.shared.HasMaxIter

Methods inherited from interface org.apache.spark.ml.param.shared.HasFeaturesCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasSeed

Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasTol

Methods inherited from interface org.apache.spark.ml.param.Params

Methods inherited from interface org.apache.spark.ml.util.Identifiable

Methods inherited from interface org.apache.spark.ml.util.DefaultParamsWritable

Methods inherited from interface org.apache.spark.ml.util.MLWritable

Methods inherited from interface org.apache.spark.internal.Logging

Constructor Detail

KMeans

KMeans

Method Detail

load

toString

params

explainParam

explainParams

isSet

isDefined

hasParam

getParam

set

get

clear

getOrDefault

getDefault

hasDefault

extractParamMap

extractParamMap

maxIter

getMaxIter

featuresCol

getFeaturesCol

seed

getSeed

predictionCol

getPredictionCol

tol

getTol

k

getK

initMode

getInitMode

initSteps

getInitSteps

save

write

uid

copy

setFeaturesCol

setPredictionCol

setK

setInitMode

setInitSteps

setMaxIter

setTol

setSeed

fit

transformSchema

k

getK

initMode

getInitMode

initSteps

getInitSteps

validateAndTransformSchema