public final class Binarizer extends Transformer implements HasThreshold, HasThresholds, HasInputCol, HasOutputCol, HasInputCols, HasOutputCols, DefaultParamsWritable
Since 3.0.0,
Binarize 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
threshold parameter is used for single column usage, and thresholds is for multiple
columns.
| Modifier and Type | Method and Description |
|---|---|
Binarizer |
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.
|
StringArrayParam |
inputCols()
Param for input column names.
|
static Binarizer |
load(String path) |
Param<String> |
outputCol()
Param for output column name.
|
StringArrayParam |
outputCols()
Param for output column names.
|
static MLReader<T> |
read() |
Binarizer |
setInputCol(String value) |
Binarizer |
setInputCols(String[] value) |
Binarizer |
setOutputCol(String value) |
Binarizer |
setOutputCols(String[] value) |
Binarizer |
setThreshold(double value) |
Binarizer |
setThresholds(double[] value) |
DoubleParam |
threshold()
Param for threshold used to binarize continuous features.
|
DoubleArrayParam |
thresholds()
Array of threshold used to binarize continuous features.
|
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.
|
transform, transform, transformparamsgetThresholdgetThresholdsgetInputColgetOutputColgetInputColsgetOutputColsclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwnwritesaveinitializeForcefully, initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarningpublic static Binarizer load(String path)
public static MLReader<T> read()
public final StringArrayParam outputCols()
HasOutputColsoutputCols in interface HasOutputColspublic final StringArrayParam inputCols()
HasInputColsinputCols in interface HasInputColspublic final Param<String> outputCol()
HasOutputColoutputCol in interface HasOutputColpublic final Param<String> inputCol()
HasInputColinputCol in interface HasInputColpublic String uid()
Identifiableuid in interface Identifiablepublic DoubleParam threshold()
threshold in interface HasThresholdpublic Binarizer setThreshold(double value)
public DoubleArrayParam thresholds()
thresholds in interface HasThresholdspublic Binarizer setThresholds(double[] value)
public Binarizer setInputCol(String value)
public Binarizer setOutputCol(String value)
public Binarizer setInputCols(String[] value)
public Binarizer setOutputCols(String[] 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 Binarizer copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Transformerextra - (undocumented)public String toString()
toString in interface IdentifiabletoString in class Object