Package org.apache.spark.ml.fpm
Interface FPGrowthParams
- All Superinterfaces:
HasPredictionCol
,Identifiable
,Params
,Serializable
- All Known Implementing Classes:
FPGrowth
,FPGrowthModel
Common params for FPGrowth and FPGrowthModel
-
Method Summary
Modifier and TypeMethodDescriptiondouble
double
int
itemsCol()
Items column name.Minimal confidence for generating Association Rule.Minimal support level of the frequent pattern.Number of partitions (at least 1) used by parallel FP-growth.validateAndTransformSchema
(StructType schema) Validates and transforms the input schema.Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol
getPredictionCol, predictionCol
Methods inherited from interface org.apache.spark.ml.util.Identifiable
toString, uid
Methods inherited from interface org.apache.spark.ml.param.Params
clear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
-
Method Details
-
getItemsCol
String getItemsCol() -
getMinConfidence
double getMinConfidence() -
getMinSupport
double getMinSupport() -
getNumPartitions
int getNumPartitions() -
itemsCol
Items column name. Default: "items"- Returns:
- (undocumented)
-
minConfidence
DoubleParam minConfidence()Minimal confidence for generating Association Rule. minConfidence will not affect the mining for frequent itemsets, but will affect the association rules generation. Default: 0.8- Returns:
- (undocumented)
-
minSupport
DoubleParam minSupport()Minimal support level of the frequent pattern. [0.0, 1.0]. Any pattern that appears more than (minSupport * size-of-the-dataset) times will be output in the frequent itemsets. Default: 0.3- Returns:
- (undocumented)
-
numPartitions
IntParam numPartitions()Number of partitions (at least 1) used by parallel FP-growth. By default the param is not set, and partition number of the input dataset is used.- Returns:
- (undocumented)
-
validateAndTransformSchema
Validates and transforms the input schema.- Parameters:
schema
- input schema- Returns:
- output schema
-