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.
|
static MaxAbsScalerModel |
load(String path) |
Vector |
maxAbs() |
static MLReader<MaxAbsScalerModel> |
read() |
MaxAbsScalerModel |
setInputCol(String value) |
MaxAbsScalerModel |
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, transform
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
validateAndTransformSchema
getInputCol, inputCol
getOutputCol, outputCol
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
save
initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning
public static MLReader<MaxAbsScalerModel> read()
public static MaxAbsScalerModel load(String path)
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
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 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