Package org.apache.spark.ml.clustering
Interface PowerIterationClusteringParams
- All Superinterfaces:
- HasMaxIter,- HasWeightCol,- Identifiable,- Params,- Serializable
- All Known Implementing Classes:
- PowerIterationClustering
Common params for PowerIterationClustering
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Method SummaryMethods inherited from interface org.apache.spark.ml.param.shared.HasMaxItergetMaxIter, maxIterMethods inherited from interface org.apache.spark.ml.param.shared.HasWeightColgetWeightCol, weightColMethods inherited from interface org.apache.spark.ml.util.IdentifiabletoString, uidMethods inherited from interface org.apache.spark.ml.param.Paramsclear, copy, 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
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Method Details- 
dstColName of the input column for destination vertex IDs. Default: "dst"- Returns:
- (undocumented)
 
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getDstColString getDstCol()
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getInitModeString getInitMode()
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getKint getK()
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getSrcColString getSrcCol()
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initModeParam for the initialization algorithm. This can be either "random" to use a random vector as vertex properties, or "degree" to use a normalized sum of similarities with other vertices. Default: random.- Returns:
- (undocumented)
 
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kIntParam k()The number of clusters to create (k). Must be > 1. Default: 2.- Returns:
- (undocumented)
 
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srcColParam for the name of the input column for source vertex IDs. Default: "src"- Returns:
- (undocumented)
 
 
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