public class MinMaxScalerModel extends Model<MinMaxScalerModel> implements 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 |
---|---|
static Params |
clear(Param<?> param) |
MinMaxScalerModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
static String |
explainParam(Param<?> param) |
static String |
explainParams() |
static ParamMap |
extractParamMap() |
static ParamMap |
extractParamMap(ParamMap extra) |
static <T> scala.Option<T> |
get(Param<T> param) |
static <T> scala.Option<T> |
getDefault(Param<T> param) |
static String |
getInputCol() |
static double |
getMax() |
double |
getMax() |
static double |
getMin() |
double |
getMin() |
static <T> T |
getOrDefault(Param<T> param) |
static String |
getOutputCol() |
static Param<Object> |
getParam(String paramName) |
static <T> boolean |
hasDefault(Param<T> param) |
static boolean |
hasParam(String paramName) |
static boolean |
hasParent() |
static Param<String> |
inputCol() |
static boolean |
isDefined(Param<?> param) |
static boolean |
isSet(Param<?> param) |
static MinMaxScalerModel |
load(String path) |
static DoubleParam |
max() |
DoubleParam |
max()
upper bound after transformation, shared by all features
Default: 1.0
|
static DoubleParam |
min() |
DoubleParam |
min()
lower bound after transformation, shared by all features
Default: 0.0
|
Vector |
originalMax() |
Vector |
originalMin() |
static Param<String> |
outputCol() |
static Param<?>[] |
params() |
static void |
parent_$eq(Estimator<M> x$1) |
static Estimator<M> |
parent() |
static MLReader<MinMaxScalerModel> |
read() |
static void |
save(String path) |
static <T> Params |
set(Param<T> param,
T value) |
MinMaxScalerModel |
setInputCol(String value) |
MinMaxScalerModel |
setMax(double value) |
MinMaxScalerModel |
setMin(double value) |
MinMaxScalerModel |
setOutputCol(String value) |
static M |
setParent(Estimator<M> parent) |
static String |
toString() |
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.
|
StructType |
validateAndTransformSchema(StructType schema)
Validates and transforms the input schema.
|
MLWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transform
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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<MinMaxScalerModel> read()
public static MinMaxScalerModel load(String path)
public static String toString()
public static Param<?>[] params()
public static String explainParam(Param<?> param)
public static String explainParams()
public static final boolean isSet(Param<?> param)
public static final boolean isDefined(Param<?> param)
public static boolean hasParam(String paramName)
public static Param<Object> getParam(String paramName)
public static final <T> scala.Option<T> get(Param<T> param)
public static final <T> T getOrDefault(Param<T> param)
public static final <T> scala.Option<T> getDefault(Param<T> param)
public static final <T> boolean hasDefault(Param<T> param)
public static final ParamMap extractParamMap()
public static Estimator<M> parent()
public static void parent_$eq(Estimator<M> x$1)
public static M setParent(Estimator<M> parent)
public static boolean hasParent()
public static final Param<String> inputCol()
public static final String getInputCol()
public static final Param<String> outputCol()
public static final String getOutputCol()
public static DoubleParam min()
public static double getMin()
public static DoubleParam max()
public static double getMax()
public static void save(String path) throws java.io.IOException
java.io.IOException
public String uid()
Identifiable
uid
in interface Identifiable
public 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)
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 MinMaxScalerModel copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Model<MinMaxScalerModel>
extra
- (undocumented)public MLWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable
public DoubleParam min()
public double getMin()
public DoubleParam max()
public double getMax()
public StructType validateAndTransformSchema(StructType schema)