org.apache.spark.ml.feature

Class MinHashLSH

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Estimator<T>

org.apache.spark.ml.feature.MinHashLSH

All Implemented Interfaces:

java.io.Serializable, Logging, Params, HasSeed, DefaultParamsWritable, Identifiable, MLWritable

public class MinHashLSH
extends Estimator<T>
implements HasSeed

:: Experimental ::

LSH class for Jaccard distance.

The input can be dense or sparse vectors, but it is more efficient if it is sparse. For example, Vectors.sparse(10, Array((2, 1.0), (3, 1.0), (5, 1.0))) means there are 10 elements in the space. This set contains elements 2, 3, and 5. Also, any input vector must have at least 1 non-zero index, and all non-zero values are treated as binary "1" values.

References: Wikipedia on MinHash

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
MinHashLSH()
MinHashLSH(String uid)

Method Summary

Modifier and Type	Method and Description
static Params	clear(Param<?> param)
MinHashLSH	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	fit(Dataset<?> dataset)
T	fit(Dataset<?> dataset) Fits a model to the input data.
static M	fit(Dataset<?> dataset, ParamMap paramMap)
static scala.collection.Seq<M>	fit(Dataset<?> dataset, ParamMap[] paramMaps)
static M	fit(Dataset<?> dataset, ParamPair<?> firstParamPair, ParamPair<?>... otherParamPairs)
static M	fit(Dataset<?> dataset, ParamPair<?> firstParamPair, scala.collection.Seq<ParamPair<?>> otherParamPairs)
static <T> scala.Option<T>	get(Param<T> param)
static <T> scala.Option<T>	getDefault(Param<T> param)
static String	getInputCol()
static int	getNumHashTables()
int	getNumHashTables()
static <T> T	getOrDefault(Param<T> param)
static String	getOutputCol()
static Param<Object>	getParam(String paramName)
static long	getSeed()
static <T> boolean	hasDefault(Param<T> param)
static boolean	hasParam(String paramName)
static Param<String>	inputCol()
static boolean	isDefined(Param<?> param)
static boolean	isSet(Param<?> param)
static MinHashLSH	load(String path)
static IntParam	numHashTables()
IntParam	numHashTables() Param for the number of hash tables used in LSH OR-amplification.
static Param<String>	outputCol()
static Param<?>[]	params()
static void	save(String path)
static LongParam	seed()
static <T> Params	set(Param<T> param, T value)
MinHashLSH	setInputCol(String value)
MinHashLSH	setNumHashTables(int value)
MinHashLSH	setOutputCol(String value)
MinHashLSH	setSeed(long value)
static String	toString()
StructType	transformSchema(StructType schema) :: DeveloperApi ::
String	uid() An immutable unique ID for the object and its derivatives.
StructType	validateAndTransformSchema(StructType schema) Transform the Schema for LSH
static MLWriter	write()

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

fit, fit, fit, fit

Methods inherited from class Object

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

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

getSeed, seed

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.Identifiable

toString

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

getInputCol, inputCol

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

getOutputCol, outputCol

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

write

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

save

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

initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Constructor Detail

MinHashLSH

public MinHashLSH(String uid)

MinHashLSH

public MinHashLSH()

Method Detail

load

public static MinHashLSH load(String path)

toString

public static String toString()

params

public static Param<?>[] params()

explainParam

public static String explainParam(Param<?> param)

explainParams

public static String explainParams()

isSet

public static final boolean isSet(Param<?> param)

isDefined

public static final boolean isDefined(Param<?> param)

hasParam

public static boolean hasParam(String paramName)

getParam

public static Param<Object> getParam(String paramName)

set

public static final <T> Params set(Param<T> param,
                                   T value)

get

public static final <T> scala.Option<T> get(Param<T> param)

clear

public static final Params clear(Param<?> param)

getOrDefault

public static final <T> T getOrDefault(Param<T> param)

getDefault

public static final <T> scala.Option<T> getDefault(Param<T> param)

hasDefault

public static final <T> boolean hasDefault(Param<T> param)

extractParamMap

public static final ParamMap extractParamMap(ParamMap extra)

extractParamMap

public static final ParamMap extractParamMap()

fit

public static M fit(Dataset<?> dataset,
                    ParamPair<?> firstParamPair,
                    scala.collection.Seq<ParamPair<?>> otherParamPairs)

fit

public static M fit(Dataset<?> dataset,
                    ParamMap paramMap)

fit

public static scala.collection.Seq<M> fit(Dataset<?> dataset,
                                          ParamMap[] paramMaps)

fit

public static M fit(Dataset<?> dataset,
                    ParamPair<?> firstParamPair,
                    ParamPair<?>... otherParamPairs)

inputCol

public static final Param<String> inputCol()

getInputCol

public static final String getInputCol()

outputCol

public static final Param<String> outputCol()

getOutputCol

public static final String getOutputCol()

numHashTables

public static final IntParam numHashTables()

getNumHashTables

public static final int getNumHashTables()

save

public static void save(String path)
                 throws java.io.IOException

Throws:

java.io.IOException

write

public static MLWriter write()

fit

public static T fit(Dataset<?> dataset)

seed

public static final LongParam seed()

getSeed

public static final long getSeed()

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 MinHashLSH setInputCol(String value)

setOutputCol

public MinHashLSH setOutputCol(String value)

setNumHashTables

public MinHashLSH setNumHashTables(int value)

setSeed

public MinHashLSH setSeed(long value)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

:: DeveloperApi ::

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 MinHashLSH 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 Estimator<MinHashLSHModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

fit

public T fit(Dataset<?> dataset)

Description copied from class: Estimator

Fits a model to the input data.

Specified by:

fit in class Estimator<T extends org.apache.spark.ml.feature.LSHModel<T>>

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

getNumHashTables

public int getNumHashTables()

numHashTables

public IntParam numHashTables()

Param for the number of hash tables used in LSH OR-amplification.

LSH OR-amplification can be used to reduce the false negative rate. Higher values for this param lead to a reduced false negative rate, at the expense of added computational complexity.

Returns:

(undocumented)

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema)

Transform the Schema for LSH

Parameters:

schema - The schema of the input dataset without outputCol.

Returns:

A derived schema with outputCol added.