public class MaxAbsScalerModel extends Model<MaxAbsScalerModel> implements MaxAbsScalerParams, MLWritable
MaxAbsScaler
.
Modifier and Type | Method and Description |
---|---|
MaxAbsScalerModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
Param<String> |
inputCol()
Param for input column name.
|
static MaxAbsScalerModel |
load(String path) |
Vector |
maxAbs() |
Param<String> |
outputCol()
Param for output column name.
|
static MLReader<MaxAbsScalerModel> |
read() |
MaxAbsScalerModel |
setInputCol(String value) |
MaxAbsScalerModel |
setOutputCol(String value) |
String |
toString() |
Dataset<Row> |
transform(Dataset<?> dataset)
Transforms the input dataset.
|
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.
|
MLWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transform
params
validateAndTransformSchema
getInputCol
getOutputCol
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
save
$init$, 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_, uninitialize
public static MLReader<MaxAbsScalerModel> read()
public static MaxAbsScalerModel load(String path)
public final Param<String> outputCol()
HasOutputCol
outputCol
in interface HasOutputCol
public final Param<String> inputCol()
HasInputCol
inputCol
in interface HasInputCol
public String uid()
Identifiable
uid
in interface Identifiable
public Vector maxAbs()
public MaxAbsScalerModel setInputCol(String value)
public MaxAbsScalerModel setOutputCol(String value)
public Dataset<Row> transform(Dataset<?> dataset)
Transformer
transform
in class Transformer
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 PipelineStage
schema
- (undocumented)public MaxAbsScalerModel copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Model<MaxAbsScalerModel>
extra
- (undocumented)public MLWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable
public String toString()
toString
in interface Identifiable
toString
in class Object