Class MinHashLSH
- All Implemented Interfaces:
Serializable
,org.apache.spark.internal.Logging
,LSHParams
,Params
,HasInputCol
,HasOutputCol
,HasSeed
,DefaultParamsWritable
,Identifiable
,MLWritable
,scala.Serializable
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:
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Nested Class Summary
Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging
org.apache.spark.internal.Logging.SparkShellLoggingFilter
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptionCreates a copy of this instance with the same UID and some extra params.Fits a model to the input data.inputCol()
Param for input column name.static MinHashLSH
final IntParam
Param for the number of hash tables used in LSH OR-amplification.Param for output column name.static MLReader<T>
read()
final LongParam
seed()
Param for random seed.setInputCol
(String value) setNumHashTables
(int value) setOutputCol
(String value) setSeed
(long value) transformSchema
(StructType schema) Check transform validity and derive the output schema from the input schema.uid()
An immutable unique ID for the object and its derivatives.Methods inherited from class org.apache.spark.ml.PipelineStage
params
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface org.apache.spark.ml.util.DefaultParamsWritable
write
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.util.Identifiable
toString
Methods inherited from interface org.apache.spark.internal.Logging
initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq
Methods inherited from interface org.apache.spark.ml.feature.LSHParams
getNumHashTables, validateAndTransformSchema
Methods inherited from interface org.apache.spark.ml.util.MLWritable
save
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, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
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Constructor Details
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MinHashLSH
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MinHashLSH
public MinHashLSH()
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Method Details
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load
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read
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seed
Description copied from interface:HasSeed
Param for random seed. -
uid
Description copied from interface:Identifiable
An immutable unique ID for the object and its derivatives.- Specified by:
uid
in interfaceIdentifiable
- Returns:
- (undocumented)
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setInputCol
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setOutputCol
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setNumHashTables
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setSeed
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transformSchema
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 byParam.validate()
.Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
- Specified by:
transformSchema
in classPipelineStage
- Parameters:
schema
- (undocumented)- Returns:
- (undocumented)
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copy
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. SeedefaultCopy()
.- Specified by:
copy
in interfaceParams
- Specified by:
copy
in classEstimator<MinHashLSHModel>
- Parameters:
extra
- (undocumented)- Returns:
- (undocumented)
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fit
Description copied from class:Estimator
Fits a model to the input data. -
inputCol
Description copied from interface:HasInputCol
Param for input column name.- Specified by:
inputCol
in interfaceHasInputCol
- Returns:
- (undocumented)
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numHashTables
Description copied from interface:LSHParams
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.
- Specified by:
numHashTables
in interfaceLSHParams
- Returns:
- (undocumented)
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outputCol
Description copied from interface:HasOutputCol
Param for output column name.- Specified by:
outputCol
in interfaceHasOutputCol
- Returns:
- (undocumented)
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