From 2c9ea56db4a1f4324f1dc8fadaf2491d83eda8ca Mon Sep 17 00:00:00 2001 From: Shivaram Venkataraman Date: Thu, 18 Jul 2013 11:57:14 -0700 Subject: [PATCH] Rename classes to be called DataGenerator --- ...Generator.scala => LogisticRegressionDataGenerator.scala} | 0 ...ionGenerator.scala => RidgeRegressionDataGenerator.scala} | 5 ++--- 2 files changed, 2 insertions(+), 3 deletions(-) rename mllib/src/main/scala/spark/mllib/util/{LogisticRegressionGenerator.scala => LogisticRegressionDataGenerator.scala} (100%) rename mllib/src/main/scala/spark/mllib/util/{RidgeRegressionGenerator.scala => RidgeRegressionDataGenerator.scala} (96%) diff --git a/mllib/src/main/scala/spark/mllib/util/LogisticRegressionGenerator.scala b/mllib/src/main/scala/spark/mllib/util/LogisticRegressionDataGenerator.scala similarity index 100% rename from mllib/src/main/scala/spark/mllib/util/LogisticRegressionGenerator.scala rename to mllib/src/main/scala/spark/mllib/util/LogisticRegressionDataGenerator.scala diff --git a/mllib/src/main/scala/spark/mllib/util/RidgeRegressionGenerator.scala b/mllib/src/main/scala/spark/mllib/util/RidgeRegressionDataGenerator.scala similarity index 96% rename from mllib/src/main/scala/spark/mllib/util/RidgeRegressionGenerator.scala rename to mllib/src/main/scala/spark/mllib/util/RidgeRegressionDataGenerator.scala index 6861913dc7..c5b8a29942 100644 --- a/mllib/src/main/scala/spark/mllib/util/RidgeRegressionGenerator.scala +++ b/mllib/src/main/scala/spark/mllib/util/RidgeRegressionDataGenerator.scala @@ -23,8 +23,7 @@ import org.jblas.DoubleMatrix import spark.{RDD, SparkContext} - -object RidgeRegressionGenerator { +object RidgeRegressionDataGenerator { /** * Generate an RDD containing test data used for RidgeRegression. This function generates @@ -82,7 +81,7 @@ object RidgeRegressionGenerator { val parts: Int = if (args.length > 4) args(4).toInt else 2 val eps = 10 - val sc = new SparkContext(sparkMaster, "RidgeRegressionGenerator") + val sc = new SparkContext(sparkMaster, "RidgeRegressionDataGenerator") val data = generateRidgeRDD(sc, nexamples, nfeatures, eps, parts) MLUtils.saveLabeledData(data, outputPath)