public class BisectingKMeans extends Estimator<BisectingKMeansModel> implements BisectingKMeansParams, DefaultParamsWritable
k leaf clusters in total or no leaf clusters are divisible.
The bisecting steps of clusters on the same level are grouped together to increase parallelism.
If bisecting all divisible clusters on the bottom level would result more than k leaf clusters,
larger clusters get higher priority.
| Constructor and Description |
|---|
BisectingKMeans() |
BisectingKMeans(String uid) |
| Modifier and Type | Method and Description |
|---|---|
BisectingKMeans |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
BisectingKMeansModel |
fit(Dataset<?> dataset)
Fits a model to the input data.
|
static BisectingKMeans |
load(String path) |
static MLReader<T> |
read() |
BisectingKMeans |
setDistanceMeasure(String value) |
BisectingKMeans |
setFeaturesCol(String value) |
BisectingKMeans |
setK(int value) |
BisectingKMeans |
setMaxIter(int value) |
BisectingKMeans |
setMinDivisibleClusterSize(double value) |
BisectingKMeans |
setPredictionCol(String value) |
BisectingKMeans |
setSeed(long value) |
StructType |
transformSchema(StructType schema)
:: DeveloperApi ::
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitgetK, getMinDivisibleClusterSize, k, minDivisibleClusterSize, validateAndTransformSchemagetMaxIter, maxIterfeaturesCol, getFeaturesColgetPredictionCol, predictionColdistanceMeasure, getDistanceMeasureclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoStringwritesaveinitializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarningpublic BisectingKMeans(String uid)
public BisectingKMeans()
public static BisectingKMeans load(String path)
public static MLReader<T> read()
public String uid()
Identifiableuid in interface Identifiablepublic BisectingKMeans copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Estimator<BisectingKMeansModel>extra - (undocumented)public BisectingKMeans setFeaturesCol(String value)
public BisectingKMeans setPredictionCol(String value)
public BisectingKMeans setK(int value)
public BisectingKMeans setMaxIter(int value)
public BisectingKMeans setSeed(long value)
public BisectingKMeans setMinDivisibleClusterSize(double value)
public BisectingKMeans setDistanceMeasure(String value)
public BisectingKMeansModel fit(Dataset<?> dataset)
Estimatorfit in class Estimator<BisectingKMeansModel>dataset - (undocumented)public StructType transformSchema(StructType schema)
PipelineStageCheck 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.
transformSchema in class PipelineStageschema - (undocumented)