public final class Bucketizer extends Model<Bucketizer> implements HasHandleInvalid, HasInputCol, HasOutputCol, HasInputCols, HasOutputCols, DefaultParamsWritable
Bucketizer
maps a column of continuous features to a column of feature buckets.
Since 2.3.0,
Bucketizer
can map multiple columns at once by setting the inputCols
parameter. Note that
when both the inputCol
and inputCols
parameters are set, an Exception will be thrown. The
splits
parameter is only used for single column usage, and splitsArray
is for multiple
columns.
Constructor and Description |
---|
Bucketizer() |
Bucketizer(String uid) |
Modifier and Type | Method and Description |
---|---|
static Params |
clear(Param<?> param) |
Bucketizer |
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 |
getHandleInvalid() |
static String |
getInputCol() |
static String[] |
getInputCols() |
static <T> T |
getOrDefault(Param<T> param) |
static String |
getOutputCol() |
static String[] |
getOutputCols() |
static Param<Object> |
getParam(String paramName) |
double[] |
getSplits() |
double[][] |
getSplitsArray() |
Param<String> |
handleInvalid()
Param for how to handle invalid entries.
|
static <T> boolean |
hasDefault(Param<T> param) |
static boolean |
hasParam(String paramName) |
static boolean |
hasParent() |
static Param<String> |
inputCol() |
static StringArrayParam |
inputCols() |
static boolean |
isDefined(Param<?> param) |
static boolean |
isSet(Param<?> param) |
static Bucketizer |
load(String path) |
static Param<String> |
outputCol() |
static StringArrayParam |
outputCols() |
static Param<?>[] |
params() |
static void |
parent_$eq(Estimator<M> x$1) |
static Estimator<M> |
parent() |
static void |
save(String path) |
static <T> Params |
set(Param<T> param,
T value) |
Bucketizer |
setHandleInvalid(String value) |
Bucketizer |
setInputCol(String value) |
Bucketizer |
setInputCols(String[] value) |
Bucketizer |
setOutputCol(String value) |
Bucketizer |
setOutputCols(String[] value) |
static M |
setParent(Estimator<M> parent) |
Bucketizer |
setSplits(double[] value) |
Bucketizer |
setSplitsArray(double[][] value) |
DoubleArrayParam |
splits()
Parameter for mapping continuous features into buckets.
|
DoubleArrayArrayParam |
splitsArray()
Parameter for specifying multiple splits parameters.
|
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.
|
MLWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transform
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getHandleInvalid
getInputCol, inputCol
getOutputCol, outputCol
getInputCols, inputCols
getOutputCols, outputCols
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 Bucketizer 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 String getHandleInvalid()
public static final Param<String> inputCol()
public static final String getInputCol()
public static final Param<String> outputCol()
public static final String getOutputCol()
public static final StringArrayParam inputCols()
public static final String[] getInputCols()
public static final StringArrayParam outputCols()
public static final String[] getOutputCols()
public static void save(String path) throws java.io.IOException
java.io.IOException
public String uid()
Identifiable
uid
in interface Identifiable
public DoubleArrayParam splits()
See also handleInvalid
, which can optionally create an additional bucket for NaN values.
public double[] getSplits()
public Bucketizer setSplits(double[] value)
public Bucketizer setInputCol(String value)
public Bucketizer setOutputCol(String value)
public Param<String> handleInvalid()
handleInvalid
in interface HasHandleInvalid
public Bucketizer setHandleInvalid(String value)
public DoubleArrayArrayParam splitsArray()
public double[][] getSplitsArray()
public Bucketizer setSplitsArray(double[][] value)
public Bucketizer setInputCols(String[] value)
public Bucketizer setOutputCols(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 Bucketizer copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Model<Bucketizer>
extra
- (undocumented)public MLWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface DefaultParamsWritable
write
in interface MLWritable