org.apache.spark.ml.feature

Class IDFModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

org.apache.spark.ml.Model<IDFModel>

org.apache.spark.ml.feature.IDFModel

All Implemented Interfaces:

java.io.Serializable, org.apache.spark.internal.Logging, IDFBase, Params, HasInputCol, HasOutputCol, Identifiable, MLWritable

public class IDFModel
extends Model<IDFModel>
implements IDFBase, MLWritable

Model fitted by IDF.

See Also:

Serialized Form

Method Summary

Modifier and Type	Method and Description
IDFModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
long[]	docFreq() Returns the document frequency
Vector	idf() Returns the IDF vector.
Param<String>	inputCol() Param for input column name.
static IDFModel	load(String path)
IntParam	minDocFreq() The minimum number of documents in which a term should appear.
long	numDocs() Returns number of documents evaluated to compute idf
Param<String>	outputCol() Param for output column name.
static MLReader<IDFModel>	read()
IDFModel	setInputCol(String value)
IDFModel	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.

Methods inherited from class org.apache.spark.ml.Model

hasParent, parent, setParent

Methods inherited from class org.apache.spark.ml.Transformer

transform, transform, transform

Methods inherited from class org.apache.spark.ml.PipelineStage

params

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.apache.spark.ml.feature.IDFBase

getMinDocFreq, validateAndTransformSchema

Methods inherited from interface org.apache.spark.ml.param.shared.HasInputCol

getInputCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasOutputCol

getOutputCol

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.util.MLWritable

save

Methods inherited from interface org.apache.spark.internal.Logging

$init$, 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

Method Detail

read

public static MLReader<IDFModel> read()

load

public static IDFModel load(String path)

minDocFreq

public final IntParam minDocFreq()

Description copied from interface: IDFBase

The minimum number of documents in which a term should appear. Default: 0

Specified by:

minDocFreq in interface IDFBase

Returns:

(undocumented)

outputCol

public final Param<String> outputCol()

Description copied from interface: HasOutputCol

Param for output column name.

Specified by:

outputCol in interface HasOutputCol

Returns:

(undocumented)

inputCol

public final Param<String> inputCol()

Description copied from interface: HasInputCol

Param for input column name.

Specified by:

inputCol in interface HasInputCol

Returns:

(undocumented)

uid

public String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

Specified by:

uid in interface Identifiable

Returns:

(undocumented)

setInputCol

public IDFModel setInputCol(String value)

setOutputCol

public IDFModel setOutputCol(String value)

transform

public Dataset<Row> transform(Dataset<?> dataset)

Description copied from class: Transformer

Transforms the input dataset.

Specified by:

transform in class Transformer

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: 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.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

copy

public IDFModel copy(ParamMap extra)

Description copied from interface: Params

Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Model<IDFModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

idf

public Vector idf()

Returns the IDF vector.

docFreq

public long[] docFreq()

Returns the document frequency

numDocs

public long numDocs()

Returns number of documents evaluated to compute idf

write

public MLWriter write()

Description copied from interface: MLWritable

Returns an MLWriter instance for this ML instance.

Specified by:

write in interface MLWritable

Returns:

(undocumented)

toString

public String toString()

Specified by:

toString in interface Identifiable

Overrides:

toString in class Object