Package org.apache.spark.ml.feature
Class MinMaxScalerModel
- All Implemented Interfaces:
- Serializable,- org.apache.spark.internal.Logging,- MinMaxScalerParams,- Params,- HasInputCol,- HasOutputCol,- Identifiable,- MLWritable
public class MinMaxScalerModel
extends Model<MinMaxScalerModel>
implements MinMaxScalerParams, MLWritable
Model fitted by 
MinMaxScaler.
 param: originalMin min value for each original column during fitting param: originalMax max value for each original column during fitting
- See Also:
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Nested Class SummaryNested ClassesNested classes/interfaces inherited from interface org.apache.spark.internal.Loggingorg.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter
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Method SummaryModifier and TypeMethodDescriptionCreates a copy of this instance with the same UID and some extra params.inputCol()Param for input column name.static MinMaxScalerModelmax()upper bound after transformation, shared by all features Default: 1.0min()lower bound after transformation, shared by all features Default: 0.0Param for output column name.static MLReader<MinMaxScalerModel>read()setInputCol(String value) setMax(double value) setMin(double value) setOutputCol(String value) toString()Transforms the input dataset.transformSchema(StructType schema) Check transform validity and derive the output schema from the input schema.uid()An immutable unique ID for the object and its derivatives.write()Returns anMLWriterinstance for this ML instance.Methods inherited from class org.apache.spark.ml.Transformertransform, transform, transformMethods inherited from class org.apache.spark.ml.PipelineStageparamsMethods inherited from class java.lang.Objectequals, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface org.apache.spark.ml.param.shared.HasInputColgetInputColMethods inherited from interface org.apache.spark.ml.param.shared.HasOutputColgetOutputColMethods inherited from interface org.apache.spark.internal.LogginginitializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, MDC, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContextMethods inherited from interface org.apache.spark.ml.feature.MinMaxScalerParamsgetMax, getMin, validateAndTransformSchemaMethods inherited from interface org.apache.spark.ml.util.MLWritablesaveMethods inherited from interface org.apache.spark.ml.param.Paramsclear, copyValues, defaultCopy, defaultParamMap, estimateMatadataSize, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
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Method Details- 
read
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load
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minDescription copied from interface:MinMaxScalerParamslower bound after transformation, shared by all features Default: 0.0- Specified by:
- minin interface- MinMaxScalerParams
- Returns:
- (undocumented)
 
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maxDescription copied from interface:MinMaxScalerParamsupper bound after transformation, shared by all features Default: 1.0- Specified by:
- maxin interface- MinMaxScalerParams
- Returns:
- (undocumented)
 
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outputColDescription copied from interface:HasOutputColParam for output column name.- Specified by:
- outputColin interface- HasOutputCol
- Returns:
- (undocumented)
 
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inputColDescription copied from interface:HasInputColParam for input column name.- Specified by:
- inputColin interface- HasInputCol
- Returns:
- (undocumented)
 
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uidDescription copied from interface:IdentifiableAn immutable unique ID for the object and its derivatives.- Specified by:
- uidin interface- Identifiable
- Returns:
- (undocumented)
 
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originalMin
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originalMax
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setInputCol
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setOutputCol
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setMin
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setMax
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transformDescription copied from class:TransformerTransforms the input dataset.- Specified by:
- transformin class- Transformer
- Parameters:
- dataset- (undocumented)
- Returns:
- (undocumented)
 
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transformSchemaDescription copied from class:PipelineStageCheck transform validity and derive the output schema from the input schema.We check validity for interactions between parameters during transformSchemaand raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled byParam.validate().Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks. - Specified by:
- transformSchemain class- PipelineStage
- Parameters:
- schema- (undocumented)
- Returns:
- (undocumented)
 
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copyDescription copied from interface:ParamsCreates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. SeedefaultCopy().- Specified by:
- copyin interface- Params
- Specified by:
- copyin class- Model<MinMaxScalerModel>
- Parameters:
- extra- (undocumented)
- Returns:
- (undocumented)
 
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writeDescription copied from interface:MLWritableReturns anMLWriterinstance for this ML instance.- Specified by:
- writein interface- MLWritable
- Returns:
- (undocumented)
 
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toString- Specified by:
- toStringin interface- Identifiable
- Overrides:
- toStringin class- Object
 
 
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