Package org.apache.spark.ml.feature
Class MinMaxScalerModel
- All Implemented Interfaces:
Serializable
,org.apache.spark.internal.Logging
,MinMaxScalerParams
,Params
,HasInputCol
,HasOutputCol
,Identifiable
,MLWritable
,scala.Serializable
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:
-
Nested Class Summary
Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging
org.apache.spark.internal.Logging.SparkShellLoggingFilter
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Method Summary
Modifier and TypeMethodDescriptionCreates a copy of this instance with the same UID and some extra params.inputCol()
Param for input column name.static MinMaxScalerModel
max()
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 anMLWriter
instance for this ML instance.Methods inherited from class org.apache.spark.ml.Transformer
transform, transform, transform
Methods inherited from class org.apache.spark.ml.PipelineStage
params
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
Methods inherited from interface org.apache.spark.ml.param.shared.HasInputCol
getInputCol
Methods inherited from interface org.apache.spark.ml.param.shared.HasOutputCol
getOutputCol
Methods inherited from interface org.apache.spark.internal.Logging
initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq
Methods inherited from interface org.apache.spark.ml.feature.MinMaxScalerParams
getMax, getMin, validateAndTransformSchema
Methods inherited from interface org.apache.spark.ml.util.MLWritable
save
Methods inherited from interface org.apache.spark.ml.param.Params
clear, copyValues, defaultCopy, defaultParamMap, 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
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read
-
load
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min
Description copied from interface:MinMaxScalerParams
lower bound after transformation, shared by all features Default: 0.0- Specified by:
min
in interfaceMinMaxScalerParams
- Returns:
- (undocumented)
-
max
Description copied from interface:MinMaxScalerParams
upper bound after transformation, shared by all features Default: 1.0- Specified by:
max
in interfaceMinMaxScalerParams
- Returns:
- (undocumented)
-
outputCol
Description copied from interface:HasOutputCol
Param for output column name.- Specified by:
outputCol
in interfaceHasOutputCol
- Returns:
- (undocumented)
-
inputCol
Description copied from interface:HasInputCol
Param for input column name.- Specified by:
inputCol
in interfaceHasInputCol
- Returns:
- (undocumented)
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uid
Description copied from interface:Identifiable
An immutable unique ID for the object and its derivatives.- Specified by:
uid
in interfaceIdentifiable
- 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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transform
Description copied from class:Transformer
Transforms the input dataset.- Specified by:
transform
in classTransformer
- Parameters:
dataset
- (undocumented)- Returns:
- (undocumented)
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transformSchema
Description copied from class:PipelineStage
Check 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 byParam.validate()
.Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
- Specified by:
transformSchema
in classPipelineStage
- Parameters:
schema
- (undocumented)- Returns:
- (undocumented)
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copy
Description copied from interface:Params
Creates 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:
copy
in interfaceParams
- Specified by:
copy
in classModel<MinMaxScalerModel>
- Parameters:
extra
- (undocumented)- Returns:
- (undocumented)
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write
Description copied from interface:MLWritable
Returns anMLWriter
instance for this ML instance.- Specified by:
write
in interfaceMLWritable
- Returns:
- (undocumented)
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toString
- Specified by:
toString
in interfaceIdentifiable
- Overrides:
toString
in classObject
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