diff options
3 files changed, 25 insertions, 9 deletions
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionExample.scala index b12f833ce9..3cf193f353 100644 --- a/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionExample.scala +++ b/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionExample.scala @@ -145,9 +145,9 @@ object LogisticRegressionExample { val elapsedTime = (System.nanoTime() - startTime) / 1e9 println(s"Training time: $elapsedTime seconds") - val lirModel = pipelineModel.stages.last.asInstanceOf[LogisticRegressionModel] + val lorModel = pipelineModel.stages.last.asInstanceOf[LogisticRegressionModel] // Print the weights and intercept for logistic regression. - println(s"Weights: ${lirModel.weights} Intercept: ${lirModel.intercept}") + println(s"Weights: ${lorModel.weights} Intercept: ${lorModel.intercept}") println("Training data results:") DecisionTreeExample.evaluateClassificationModel(pipelineModel, training, "indexedLabel") diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala index 557119f7b1..3523f18043 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala @@ -213,9 +213,9 @@ private[spark] object BLAS extends Serializable with Logging { def scal(a: Double, x: Vector): Unit = { x match { case sx: SparseVector => - f2jBLAS.dscal(sx.values.size, a, sx.values, 1) + f2jBLAS.dscal(sx.values.length, a, sx.values, 1) case dx: DenseVector => - f2jBLAS.dscal(dx.values.size, a, dx.values, 1) + f2jBLAS.dscal(dx.values.length, a, dx.values, 1) case _ => throw new IllegalArgumentException(s"scal doesn't support vector type ${x.getClass}.") } diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala index 52d6468a72..7c5cfa7bd8 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala @@ -270,12 +270,28 @@ object MLUtils { * Returns a new vector with `1.0` (bias) appended to the input vector. */ def appendBias(vector: Vector): Vector = { - val vector1 = vector.toBreeze match { - case dv: BDV[Double] => BDV.vertcat(dv, new BDV[Double](Array(1.0))) - case sv: BSV[Double] => BSV.vertcat(sv, new BSV[Double](Array(0), Array(1.0), 1)) - case v: Any => throw new IllegalArgumentException("Do not support vector type " + v.getClass) + vector match { + case dv: DenseVector => + val inputValues = dv.values + val inputLength = inputValues.length + val outputValues = Array.ofDim[Double](inputLength + 1) + System.arraycopy(inputValues, 0, outputValues, 0, inputLength) + outputValues(inputLength) = 1.0 + Vectors.dense(outputValues) + case sv: SparseVector => + val inputValues = sv.values + val inputIndices = sv.indices + val inputValuesLength = inputValues.length + val dim = sv.size + val outputValues = Array.ofDim[Double](inputValuesLength + 1) + val outputIndices = Array.ofDim[Int](inputValuesLength + 1) + System.arraycopy(inputValues, 0, outputValues, 0, inputValuesLength) + System.arraycopy(inputIndices, 0, outputIndices, 0, inputValuesLength) + outputValues(inputValuesLength) = 1.0 + outputIndices(inputValuesLength) = dim + Vectors.sparse(dim + 1, outputIndices, outputValues) + case _ => throw new IllegalArgumentException(s"Do not support vector type ${vector.getClass}") } - Vectors.fromBreeze(vector1) } /** |