public class MaxAbsScaler extends Estimator<MaxAbsScalerModel> implements MaxAbsScalerParams, DefaultParamsWritable
| Constructor and Description |
|---|
MaxAbsScaler() |
MaxAbsScaler(String uid) |
| Modifier and Type | Method and Description |
|---|---|
MaxAbsScaler |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
MaxAbsScalerModel |
fit(Dataset<?> dataset)
Fits a model to the input data.
|
Param<String> |
inputCol()
Param for input column name.
|
static MaxAbsScaler |
load(String path) |
Param<String> |
outputCol()
Param for output column name.
|
static MLReader<T> |
read() |
MaxAbsScaler |
setInputCol(String value) |
MaxAbsScaler |
setOutputCol(String value) |
StructType |
transformSchema(StructType schema)
Check transform validity and derive the output schema from the input schema.
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
paramsequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitvalidateAndTransformSchemagetInputColgetOutputColclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoStringwritesave$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitializepublic static MaxAbsScaler load(String path)
public static MLReader<T> read()
public final Param<String> outputCol()
HasOutputColoutputCol in interface HasOutputColpublic final Param<String> inputCol()
HasInputColinputCol in interface HasInputColpublic String uid()
Identifiableuid in interface Identifiablepublic MaxAbsScaler setInputCol(String value)
public MaxAbsScaler setOutputCol(String value)
public MaxAbsScalerModel fit(Dataset<?> dataset)
Estimatorfit in class Estimator<MaxAbsScalerModel>dataset - (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
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)public MaxAbsScaler copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Estimator<MaxAbsScalerModel>extra - (undocumented)