diff options
-rw-r--r-- | mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala | 2 | ||||
-rw-r--r-- | mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala | 44 |
2 files changed, 42 insertions, 4 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala index 486bdbfa9c..84d3c7cebd 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala @@ -84,7 +84,7 @@ class LogisticRegressionWithSGD private ( extends GeneralizedLinearAlgorithm[LogisticRegressionModel] with Serializable { private val gradient = new LogisticGradient() - private val updater = new SimpleUpdater() + private val updater = new SquaredL2Updater() override val optimizer = new GradientDescent(gradient, updater) .setStepSize(stepSize) .setNumIterations(numIterations) diff --git a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala index 862178694a..e954baaf7d 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala @@ -43,7 +43,7 @@ object LogisticRegressionSuite { offset: Double, scale: Double, nPoints: Int, - seed: Int): Seq[LabeledPoint] = { + seed: Int): Seq[LabeledPoint] = { val rnd = new Random(seed) val x1 = Array.fill[Double](nPoints)(rnd.nextGaussian()) @@ -58,12 +58,15 @@ object LogisticRegressionSuite { } class LogisticRegressionSuite extends FunSuite with LocalSparkContext with Matchers { - def validatePrediction(predictions: Seq[Double], input: Seq[LabeledPoint]) { + def validatePrediction( + predictions: Seq[Double], + input: Seq[LabeledPoint], + expectedAcc: Double = 0.83) { val numOffPredictions = predictions.zip(input).count { case (prediction, expected) => prediction != expected.label } // At least 83% of the predictions should be on. - ((input.length - numOffPredictions).toDouble / input.length) should be > 0.83 + ((input.length - numOffPredictions).toDouble / input.length) should be > expectedAcc } // Test if we can correctly learn A, B where Y = logistic(A + B*X) @@ -155,6 +158,41 @@ class LogisticRegressionSuite extends FunSuite with LocalSparkContext with Match validatePrediction(validationData.map(row => model.predict(row.features)), validationData) } + test("logistic regression with initial weights and non-default regularization parameter") { + val nPoints = 10000 + val A = 2.0 + val B = -1.5 + + val testData = LogisticRegressionSuite.generateLogisticInput(A, B, nPoints, 42) + + val initialB = -1.0 + val initialWeights = Vectors.dense(initialB) + + val testRDD = sc.parallelize(testData, 2) + testRDD.cache() + + // Use half as many iterations as the previous test. + val lr = new LogisticRegressionWithSGD().setIntercept(true) + lr.optimizer. + setStepSize(10.0). + setNumIterations(10). + setRegParam(1.0) + + val model = lr.run(testRDD, initialWeights) + + // Test the weights + assert(model.weights(0) ~== -430000.0 relTol 20000.0) + assert(model.intercept ~== 370000.0 relTol 20000.0) + + val validationData = LogisticRegressionSuite.generateLogisticInput(A, B, nPoints, 17) + val validationRDD = sc.parallelize(validationData, 2) + // Test prediction on RDD. + validatePrediction(model.predict(validationRDD.map(_.features)).collect(), validationData, 0.8) + + // Test prediction on Array. + validatePrediction(validationData.map(row => model.predict(row.features)), validationData, 0.8) + } + test("logistic regression with initial weights with LBFGS") { val nPoints = 10000 val A = 2.0 |