Class: Spark::Mllib::KMeans
- Inherits:
-
Object
- Object
- Spark::Mllib::KMeans
- Defined in:
- lib/spark/mllib/clustering/kmeans.rb
Class Method Summary collapse
-
.train(rdd, k, max_iterations: 100, runs: 1, initialization_mode: 'k-means||', seed: nil) ⇒ Object
Trains a k-means model using the given set of parameters.
Class Method Details
.train(rdd, k, max_iterations: 100, runs: 1, initialization_mode: 'k-means||', seed: nil) ⇒ Object
Trains a k-means model using the given set of parameters.
Arguments:
- rdd
-
The training data, an RDD of Vectors.
- k
-
Number of clusters.
- max_iterations
-
Max number of iterations.
- runs
-
Number of parallel runs, defaults to 1. The best model is returned.
- initialization_mode
-
Initialization model, either “random” or “k-means||” (default).
- seed
-
Random seed value for cluster initialization.
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# File 'lib/spark/mllib/clustering/kmeans.rb', line 110 def self.train(rdd, k, max_iterations: 100, runs: 1, initialization_mode: 'k-means||', seed: nil) # Call returns KMeansModel Spark.jb.call(RubyMLLibAPI.new, 'trainKMeansModel', rdd, k, max_iterations, runs, initialization_mode, Spark.jb.to_long(seed)) end |