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Lewuathe committed Mar 16, 2015
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7 changes: 4 additions & 3 deletions docs/mllib-optimization.md
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Expand Up @@ -203,9 +203,10 @@ regularization, as well as L2 regularizer.
recommended.
* `maxNumIterations` is the maximal number of iterations that L-BFGS can be run.
* `regParam` is the regularization parameter when using regularization.
* `convergenceTol` designates the end of iterations based on relative comparison
of adjusted values. This value is used by [Breeze LBFGS](https://github.com/scalanlp/breeze),
and it looks at both average improvement and the norm of gradient.
* `convergenceTol` controls how much relative change is still allowed when L-BFGS
is considered to converge. This must be nonnegative. Lower values are less tolerant and
therefore generally cause more iterations to be run. This value looks at both average
improvement and the norm of gradient inside [Breeze LBFGS](https://github.com/scalanlp/breeze/blob/master/math/src/main/scala/breeze/optimize/LBFGS.scala).

The `return` is a tuple containing two elements. The first element is a column matrix
containing weights for every feature, and the second element is an array containing
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Expand Up @@ -60,6 +60,8 @@ class LBFGS(private var gradient: Gradient, private var updater: Updater)
/**
* Set the convergence tolerance of iterations for L-BFGS. Default 1E-4.
* Smaller value will lead to higher accuracy with the cost of more iterations.
* This value must be nonnegative. Lower convergence tolerance is less tolerant
* therefore generally cause more iterations to be run.
*/
def setConvergenceTol(tolerance: Double): this.type = {
this.convergenceTol = tolerance
Expand Down Expand Up @@ -142,7 +144,9 @@ object LBFGS extends Logging {
* one single data example)
* @param updater - Updater function to actually perform a gradient step in a given direction.
* @param numCorrections - The number of corrections used in the L-BFGS update.
* @param convergenceTol - The convergence tolerance of iterations for L-BFGS
* @param convergenceTol - The convergence tolerance of iterations for L-BFGS which is must be
* nonnegative. Lower values are less tolerant and therefore generally
* cause more iterations to be run.
* @param maxNumIterations - Maximal number of iterations that L-BFGS can be run.
* @param regParam - Regularization parameter
*
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