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Diffstat (limited to 'mllib/src/test/scala/spark/mllib/regression/LogisticRegressionSuite.scala')
-rw-r--r-- | mllib/src/test/scala/spark/mllib/regression/LogisticRegressionSuite.scala | 57 |
1 files changed, 0 insertions, 57 deletions
diff --git a/mllib/src/test/scala/spark/mllib/regression/LogisticRegressionSuite.scala b/mllib/src/test/scala/spark/mllib/regression/LogisticRegressionSuite.scala deleted file mode 100644 index 04d3400cb4..0000000000 --- a/mllib/src/test/scala/spark/mllib/regression/LogisticRegressionSuite.scala +++ /dev/null @@ -1,57 +0,0 @@ -package spark.mllib.regression - -import scala.util.Random - -import org.scalatest.BeforeAndAfterAll -import org.scalatest.FunSuite - -import spark.SparkContext -import spark.SparkContext._ - - -class LogisticRegressionSuite extends FunSuite with BeforeAndAfterAll { - val sc = new SparkContext("local", "test") - - override def afterAll() { - sc.stop() - System.clearProperty("spark.driver.port") - } - - // Test if we can correctly learn A, B where Y = logistic(A + B*X) - test("logistic regression") { - val nPoints = 10000 - val rnd = new Random(42) - - val x1 = Array.fill[Double](nPoints)(rnd.nextGaussian()) - - val A = 2.0 - val B = -1.5 - - // NOTE: if U is uniform[0, 1] then ln(u) - ln(1-u) is Logistic(0,1) - val unifRand = new scala.util.Random(45) - val rLogis = (0 until nPoints).map { i => - val u = unifRand.nextDouble() - math.log(u) - math.log(1.0-u) - } - - // y <- A + B*x + rlogis(100) - // y <- as.numeric(y > 0) - val y = (0 until nPoints).map { i => - val yVal = A + B * x1(i) + rLogis(i) - if (yVal > 0) 1.0 else 0.0 - } - - val testData = (0 until nPoints).map(i => (y(i).toDouble, Array(x1(i)))).toArray - - val testRDD = sc.parallelize(testData, 2) - testRDD.cache() - val lr = new LogisticRegression().setStepSize(10.0) - .setNumIterations(20) - - val model = lr.train(testRDD) - - val weight0 = model.weights.get(0) - assert(weight0 >= -1.60 && weight0 <= -1.40, weight0 + " not in [-1.6, -1.4]") - assert(model.intercept >= 1.9 && model.intercept <= 2.1, model.intercept + " not in [1.9, 2.1]") - } -} |