Serializable
, org.apache.spark.internal.Logging
, LSHParams
, Params
, HasInputCol
, HasOutputCol
, HasSeed
, DefaultParamsWritable
, Identifiable
, MLWritable
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
org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter
Constructors
Creates a copy of this instance with the same UID and some extra params.
Fits a model to the input data.
Param for input column name.
Param for the number of hash tables used in LSH OR-amplification.
Param for output column name.
Check transform validity and derive the output schema from the input schema.
An immutable unique ID for the object and its derivatives.
Methods inherited from interface org.apache.spark.internal.LogginginitializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext
Methods inherited from interface org.apache.spark.ml.util.MLWritablesave
Methods inherited from interface org.apache.spark.ml.param.Paramsclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
public MinHashLSH()
HasSeed
Param for random seed.
An immutable unique ID for the object and its derivatives.
uid
in interface Identifiable
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.
transformSchema
in class PipelineStage
schema
- (undocumented)
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()
.
copy
in interface Params
copy
in class Estimator<MinHashLSHModel>
extra
- (undocumented)
Fits a model to the input data.
Param for input column name.
inputCol
in interface HasInputCol
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.
numHashTables
in interface LSHParams
Param for output column name.
outputCol
in interface HasOutputCol
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4