diff options
Diffstat (limited to 'mllib')
-rw-r--r-- | mllib/src/main/scala/org/apache/spark/ml/r/GeneralizedLinearRegressionWrapper.scala | 4 | ||||
-rw-r--r-- | mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala | 40 |
2 files changed, 43 insertions, 1 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/r/GeneralizedLinearRegressionWrapper.scala b/mllib/src/main/scala/org/apache/spark/ml/r/GeneralizedLinearRegressionWrapper.scala index 0d3181d0ac..7a6ab618a1 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/r/GeneralizedLinearRegressionWrapper.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/r/GeneralizedLinearRegressionWrapper.scala @@ -69,7 +69,8 @@ private[r] object GeneralizedLinearRegressionWrapper link: String, tol: Double, maxIter: Int, - weightCol: String): GeneralizedLinearRegressionWrapper = { + weightCol: String, + regParam: Double): GeneralizedLinearRegressionWrapper = { val rFormula = new RFormula() .setFormula(formula) val rFormulaModel = rFormula.fit(data) @@ -86,6 +87,7 @@ private[r] object GeneralizedLinearRegressionWrapper .setTol(tol) .setMaxIter(maxIter) .setWeightCol(weightCol) + .setRegParam(regParam) val pipeline = new Pipeline() .setStages(Array(rFormulaModel, glr)) .fit(data) diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala index a4568e83fa..d8032c4e17 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala @@ -1034,6 +1034,46 @@ class GeneralizedLinearRegressionSuite .setFamily("gaussian") .fit(datasetGaussianIdentity.as[LabeledPoint]) } + + test("generalized linear regression: regularization parameter") { + /* + R code: + + a1 <- c(0, 1, 2, 3) + a2 <- c(5, 2, 1, 3) + b <- c(1, 0, 1, 0) + data <- as.data.frame(cbind(a1, a2, b)) + df <- suppressWarnings(createDataFrame(data)) + + for (regParam in c(0.0, 0.1, 1.0)) { + model <- spark.glm(df, b ~ a1 + a2, regParam = regParam) + print(as.vector(summary(model)$aic)) + } + + [1] 12.88188 + [1] 12.92681 + [1] 13.32836 + */ + val dataset = spark.createDataFrame(Seq( + LabeledPoint(1, Vectors.dense(5, 0)), + LabeledPoint(0, Vectors.dense(2, 1)), + LabeledPoint(1, Vectors.dense(1, 2)), + LabeledPoint(0, Vectors.dense(3, 3)) + )) + val expected = Seq(12.88188, 12.92681, 13.32836) + + var idx = 0 + for (regParam <- Seq(0.0, 0.1, 1.0)) { + val trainer = new GeneralizedLinearRegression() + .setRegParam(regParam) + .setLabelCol("label") + .setFeaturesCol("features") + val model = trainer.fit(dataset) + val actual = model.summary.aic + assert(actual ~= expected(idx) absTol 1e-4, "Model mismatch: GLM with regParam = $regParam.") + idx += 1 + } + } } object GeneralizedLinearRegressionSuite { |