From Alpine Data Labs

Author: DB Tsai

mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala

@@ -17,13 +17,12 @@
 
 package org.apache.spark.mllib.regression
 
-import breeze.linalg.{DenseVector => BDV, SparseVector => BSV}
-
 import org.apache.spark.annotation.DeveloperApi
 import org.apache.spark.{Logging, SparkException}
 import org.apache.spark.rdd.RDD
 import org.apache.spark.mllib.optimization._
 import org.apache.spark.mllib.linalg.{Vectors, Vector}
+import org.apache.spark.mllib.util.MLUtils._
 
 /**
  * :: DeveloperApi ::
@@ -124,16 +123,6 @@ abstract class GeneralizedLinearAlgorithm[M <: GeneralizedLinearModel]
     run(input, initialWeights)
   }
 
-  /** Prepends one to the input vector. */
-  private def prependOne(vector: Vector): Vector = {
-    val vector1 = vector.toBreeze match {
-      case dv: BDV[Double] => BDV.vertcat(BDV.ones[Double](1), dv)
-      case sv: BSV[Double] => BSV.vertcat(new BSV[Double](Array(0), Array(1.0), 1), sv)
-      case v: Any => throw new IllegalArgumentException("Do not support vector type " + v.getClass)
-    }
-    Vectors.fromBreeze(vector1)
-  }
-
   /**
    * Run the algorithm with the configured parameters on an input RDD
    * of LabeledPoint entries starting from the initial weights provided.
@@ -147,23 +136,23 @@ abstract class GeneralizedLinearAlgorithm[M <: GeneralizedLinearModel]
 
     // Prepend an extra variable consisting of all 1.0's for the intercept.
     val data = if (addIntercept) {
-      input.map(labeledPoint => (labeledPoint.label, prependOne(labeledPoint.features)))
+      input.map(labeledPoint => (labeledPoint.label, appendBias(labeledPoint.features)))
     } else {
       input.map(labeledPoint => (labeledPoint.label, labeledPoint.features))
     }
 
     val initialWeightsWithIntercept = if (addIntercept) {
-      prependOne(initialWeights)
+      appendBias(initialWeights)
     } else {
       initialWeights
     }
 
     val weightsWithIntercept = optimizer.optimize(data, initialWeightsWithIntercept)
 
-    val intercept = if (addIntercept) weightsWithIntercept(0) else 0.0
+    val intercept = if (addIntercept) weightsWithIntercept(weightsWithIntercept.size - 1) else 0.0
     val weights =
       if (addIntercept) {
-        Vectors.dense(weightsWithIntercept.toArray.slice(1, weightsWithIntercept.size))
+        Vectors.dense(weightsWithIntercept.toArray.slice(0, weightsWithIntercept.size - 1))
       } else {
         weightsWithIntercept
       }