<commit_before>package main.scala

import spark._
import spark.SparkContext._

import breeze.linalg._
import breeze.classify._

import breeze.data.Example

/*
* For each label, we train a 1-v-all classifier
*/
class TrainSVM(sc: SparkContext) extends Base {

  // Support generic sequences
  def train(samples : Seq[PolarExample]) : Classifier[Int, Array[Float]] = {
    SVM(samples)
  }

  // If scaling becomes an issues then we'll have to roll our own implementation.
  // Breeze is not parallel
  def train(samples : RDD[PolarExample]) : Classifier[Int, Array[Float]] = {
    train(samples.collect())
  }
}

object TrainSVM extends Base {<commit_msg>fixing the build<commit_after>package main.scala

import spark._
import spark.SparkContext._

import breeze.linalg._
import breeze.classify._

import breeze.data.Example

/*
* For each label, we train a 1-v-all classifier
*/
class TrainSVM(sc: SparkContext) extends Base {

  // Support generic sequences
  def train(samples : Seq[PolarExample]) : Classifier[Int, Array[Float]] = {
    //SVM(samples)
    null
  }

  // If scaling becomes an issues then we'll have to roll our own implementation.
  // Breeze is not parallel
  def train(samples : RDD[PolarExample]) : Classifier[Int, Array[Float]] = {
    train(samples.collect())
  }
}

object TrainSVM extends Base {
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