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[SPARK-1260]: faster construction of features with intercept #161

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[SPARK-1260]: faster construction of features with intercept #161

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a1439c2
faster construction of features with intercept
mengxr Mar 17, 2014
b5cfc53
set default weights to zeros
mengxr Mar 17, 2014
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8 changes: 4 additions & 4 deletions mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -119,7 +119,7 @@ abstract class GeneralizedLinearAlgorithm[M <: GeneralizedLinearModel]
*/
def run(input: RDD[LabeledPoint]) : M = {
val nfeatures: Int = input.first().features.length
val initialWeights = Array.fill(nfeatures)(1.0)
val initialWeights = new Array[Double](nfeatures)
run(input, initialWeights)
}

Expand All @@ -134,15 +134,15 @@ abstract class GeneralizedLinearAlgorithm[M <: GeneralizedLinearModel]
throw new SparkException("Input validation failed.")
}

// Add a extra variable consisting of all 1.0's for the intercept.
// Prepend an extra variable consisting of all 1.0's for the intercept.
val data = if (addIntercept) {
input.map(labeledPoint => (labeledPoint.label, Array(1.0, labeledPoint.features:_*)))
input.map(labeledPoint => (labeledPoint.label, labeledPoint.features.+:(1.0)))
} else {
input.map(labeledPoint => (labeledPoint.label, labeledPoint.features))
}

val initialWeightsWithIntercept = if (addIntercept) {
Array(1.0, initialWeights:_*)
initialWeights.+:(1.0)
} else {
initialWeights
}
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