public class MinMaxScaler extends Estimator<MinMaxScalerModel>
Rescaled(e_i) = \frac{e_i - E_{min}}{E_{max} - E_{min}} * (max - min) + min
For the case E_{max} == E_{min}, Rescaled(e_i) = 0.5 * (max + min) Note that since zero values will probably be transformed to non-zero values, output of the transformer will be DenseVector even for sparse input.
Constructor and Description |
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MinMaxScaler() |
MinMaxScaler(java.lang.String uid) |
Modifier and Type | Method and Description |
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MinMaxScaler |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
MinMaxScalerModel |
fit(DataFrame dataset)
Fits a model to the input data.
|
double |
getMax() |
double |
getMin() |
DoubleParam |
max()
upper bound after transformation, shared by all features
Default: 1.0
|
DoubleParam |
min()
lower bound after transformation, shared by all features
Default: 0.0
|
MinMaxScaler |
setInputCol(java.lang.String value) |
MinMaxScaler |
setMax(double value) |
MinMaxScaler |
setMin(double value) |
MinMaxScaler |
setOutputCol(java.lang.String value) |
StructType |
transformSchema(StructType schema)
:: DeveloperApi ::
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java.lang.String |
uid()
An immutable unique ID for the object and its derivatives.
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StructType |
validateAndTransformSchema(StructType schema)
Validates and transforms the input schema.
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void |
validateParams()
Validates parameter values stored internally.
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transformSchema
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
toString
initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning
public MinMaxScaler(java.lang.String uid)
public MinMaxScaler()
public java.lang.String uid()
Identifiable
uid
in interface Identifiable
public MinMaxScaler setInputCol(java.lang.String value)
public MinMaxScaler setOutputCol(java.lang.String value)
public MinMaxScaler setMin(double value)
public MinMaxScaler setMax(double value)
public MinMaxScalerModel fit(DataFrame dataset)
Estimator
fit
in class Estimator<MinMaxScalerModel>
dataset
- (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
Derives the output schema from the input schema.
transformSchema
in class PipelineStage
schema
- (undocumented)public MinMaxScaler copy(ParamMap extra)
Params
copy
in interface Params
copy
in class Estimator<MinMaxScalerModel>
extra
- (undocumented)defaultCopy()
public DoubleParam min()
public double getMin()
public DoubleParam max()
public double getMax()
public StructType validateAndTransformSchema(StructType schema)
public void validateParams()
Params
This only needs to check for interactions between parameters.
Parameter value checks which do not depend on other parameters are handled by
Param.validate()
. This method does not handle input/output column parameters;
those are checked during schema validation.
validateParams
in interface Params