Package org.apache.spark.ml.feature

Class BucketedRandomProjectionLSHModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

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

org.apache.spark.ml.feature.LSHModel<BucketedRandomProjectionLSHModel>

org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel

All Implemented Interfaces:

Serializable, org.apache.spark.internal.Logging, org.apache.spark.ml.feature.BucketedRandomProjectionLSHParams, org.apache.spark.ml.feature.LSHParams, Params, HasInputCol, HasOutputCol, Identifiable, MLWritable

public class BucketedRandomProjectionLSHModel
extends org.apache.spark.ml.feature.LSHModel<BucketedRandomProjectionLSHModel>
implements org.apache.spark.ml.feature.BucketedRandomProjectionLSHParams

Model produced by BucketedRandomProjectionLSH, where multiple random vectors are stored. The vectors are normalized to be unit vectors and each vector is used in a hash function: h_i(x) = floor(r_i.dot(x) / bucketLength) where r_i is the i-th random unit vector. The number of buckets will be (max L2 norm of input vectors) / bucketLength.

param: randMatrix A matrix with each row representing a hash function.

See Also:

• Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	BucketedRandomProjectionLSHModel.Data$

Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter

Method Summary

Modifier and Type	Method	Description
DoubleParam	bucketLength()
BucketedRandomProjectionLSHModel	copy(ParamMap extra)	Creates a copy of this instance with the same UID and some extra params.
static BucketedRandomProjectionLSHModel	load(String path)
static MLReader<BucketedRandomProjectionLSHModel>	read()
BucketedRandomProjectionLSHModel	setInputCol(String value)
BucketedRandomProjectionLSHModel	setOutputCol(String value)
String	toString()
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.feature.LSHModel

approxNearestNeighbors, approxNearestNeighbors, approxNearestNeighbors, approxSimilarityJoin, approxSimilarityJoin, getInputCol, getNumHashTables, getOutputCol, inputCol, numHashTables, org$apache$spark$ml$feature$LSHParams$_setter_$numHashTables_$eq, org$apache$spark$ml$param$shared$HasInputCol$_setter_$inputCol_$eq, org$apache$spark$ml$param$shared$HasOutputCol$_setter_$outputCol_$eq, outputCol, save, transform, transformSchema, validateAndTransformSchema

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 java.lang.Object

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

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

getBucketLength, org$apache$spark$ml$feature$BucketedRandomProjectionLSHParams$_setter_$bucketLength_$eq

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

initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, MDC, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext

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

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

Method Details

read

public static MLReader<BucketedRandomProjectionLSHModel> read()

load

public static BucketedRandomProjectionLSHModel load(String path)

bucketLength

public DoubleParam bucketLength()

Specified by:

bucketLength in interface org.apache.spark.ml.feature.BucketedRandomProjectionLSHParams

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 BucketedRandomProjectionLSHModel setInputCol(String value)

Overrides:

setInputCol in class org.apache.spark.ml.feature.LSHModel<BucketedRandomProjectionLSHModel>

setOutputCol

public BucketedRandomProjectionLSHModel setOutputCol(String value)

Overrides:

setOutputCol in class org.apache.spark.ml.feature.LSHModel<BucketedRandomProjectionLSHModel>

copy

public BucketedRandomProjectionLSHModel 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<BucketedRandomProjectionLSHModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

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