org.apache.spark.mllib.util

MFDataGenerator

object MFDataGenerator

:: DeveloperApi :: Generate RDD(s) containing data for Matrix Factorization.

This method samples training entries according to the oversampling factor 'trainSampFact', which is a multiplicative factor of the number of degrees of freedom of the matrix: rank*(m+n-rank).

It optionally samples entries for a testing matrix using 'testSampFact', the percentage of the number of training entries to use for testing.

This method takes the following inputs: sparkMaster (String) The master URL. outputPath (String) Directory to save output. m (Int) Number of rows in data matrix. n (Int) Number of columns in data matrix. rank (Int) Underlying rank of data matrix. trainSampFact (Double) Oversampling factor. noise (Boolean) Whether to add gaussian noise to training data. sigma (Double) Standard deviation of added gaussian noise. test (Boolean) Whether to create testing RDD. testSampFact (Double) Percentage of training data to use as test data.

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@DeveloperApi() @Since( "0.8.0" )
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MFDataGenerator.scala
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