Imb-sampling-ROS_and_RUS

Spark implementations of two data sampling methods (random oversampling and random undersampling) for imbalanced data.

Example (Undersampling):

Parameters

"path-to-header" "path-to-train" "number-of-partition" "name-of-majority-class" "name-of-minority-class" "pathOutput"

spark-submit --class org.apache.spark.mllib.sampling.runRUS Imb-sampling-1.0.jar hdfs://hadoop-master/datasets/data.header hdfs://hadoop-master/datasets/train.data 250 0 1 hdfs://hadoop-master/datasets/train-under.data

Example (Oversampling):

Parameters

"path-to-header" "path-to-train" "number-of-partition" "number-of-repartition" "name-of-majority-class" "name-of-minority-class" "oversampling-rate" "pathOutput"

spark-submit --class org.apache.spark.mllib.sampling.runROS Imb-sampling-1.0.jar hdfs://hadoop-master/datasets/data.header hdfs://hadoop-master/datasets/train.data 100 250 0 1 2.0 hdfs://hadoop-master/datasets/train-under.data

Credits

Developed by: Sara del Río García (srio@decsai.ugr.es)

Maintained by: Sergio Ramírez (sramirez@decsai.ugr.es) / @sramirez