public class MinMaxScalerModel extends Model<MinMaxScalerModel> implements MinMaxScalerParams, MLWritable
MinMaxScaler.
param: originalMin min value for each original column during fitting param: originalMax max value for each original column during fitting
TODO: The transformer does not yet set the metadata in the output column (SPARK-8529).
| Modifier and Type | Method and Description |
|---|---|
MinMaxScalerModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
static MinMaxScalerModel |
load(String path) |
Vector |
originalMax() |
Vector |
originalMin() |
static MLReader<MinMaxScalerModel> |
read() |
MinMaxScalerModel |
setInputCol(String value) |
MinMaxScalerModel |
setMax(double value) |
MinMaxScalerModel |
setMin(double value) |
MinMaxScalerModel |
setOutputCol(String value) |
Dataset<Row> |
transform(Dataset<?> dataset)
Transforms the input dataset.
|
StructType |
transformSchema(StructType schema)
:: DeveloperApi ::
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
MLWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transformequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitgetMax, getMin, max, min, validateAndTransformSchemagetInputCol, inputColgetOutputCol, outputColclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoStringsaveinitializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarningpublic static MLReader<MinMaxScalerModel> read()
public static MinMaxScalerModel load(String path)
public String uid()
Identifiableuid in interface Identifiablepublic Vector originalMin()
public Vector originalMax()
public MinMaxScalerModel setInputCol(String value)
public MinMaxScalerModel setOutputCol(String value)
public MinMaxScalerModel setMin(double value)
public MinMaxScalerModel setMax(double value)
public Dataset<Row> transform(Dataset<?> dataset)
Transformertransform in class Transformerdataset - (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)public MinMaxScalerModel copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Model<MinMaxScalerModel>extra - (undocumented)public MLWriter write()
MLWritableMLWriter instance for this ML instance.write in interface MLWritable