public class KMeans extends Estimator<KMeansModel> implements KMeansParams, DefaultParamsWritable
| Modifier and Type | Method and Description |
|---|---|
KMeans |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
KMeansModel |
fit(Dataset<?> dataset)
Fits a model to the input data.
|
static KMeans |
load(String path) |
static MLReader<T> |
read() |
KMeans |
setDistanceMeasure(String 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) |
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, waitgetInitMode, getInitSteps, getK, initMode, initSteps, k, 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 static KMeans load(String path)
public static MLReader<T> read()
public String uid()
Identifiableuid in interface Identifiablepublic KMeans copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Estimator<KMeansModel>extra - (undocumented)public KMeans setFeaturesCol(String value)
public KMeans setPredictionCol(String value)
public KMeans setK(int value)
public KMeans setInitMode(String value)
public KMeans setDistanceMeasure(String value)
public KMeans setInitSteps(int value)
public KMeans setMaxIter(int value)
public KMeans setTol(double value)
public KMeans setSeed(long value)
public KMeansModel fit(Dataset<?> dataset)
Estimatorfit in class Estimator<KMeansModel>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)