diff options
Diffstat (limited to 'mllib/src')
| -rw-r--r-- | mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala b/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala index fdd6716011..45dbf6044f 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala @@ -128,7 +128,7 @@ class LeastSquaresGradient extends Gradient { class HingeGradient extends Gradient { override def compute(data: Vector, label: Double, weights: Vector): (Vector, Double) = { val dotProduct = dot(data, weights) - // Our loss function with {0, 1} labels is max(0, 1 - (2y – 1) (f_w(x))) + // Our loss function with {0, 1} labels is max(0, 1 - (2y - 1) (f_w(x))) // Therefore the gradient is -(2y - 1)*x val labelScaled = 2 * label - 1.0 if (1.0 > labelScaled * dotProduct) { @@ -146,7 +146,7 @@ class HingeGradient extends Gradient { weights: Vector, cumGradient: Vector): Double = { val dotProduct = dot(data, weights) - // Our loss function with {0, 1} labels is max(0, 1 - (2y – 1) (f_w(x))) + // Our loss function with {0, 1} labels is max(0, 1 - (2y - 1) (f_w(x))) // Therefore the gradient is -(2y - 1)*x val labelScaled = 2 * label - 1.0 if (1.0 > labelScaled * dotProduct) { |