Github user MLnick commented on a diff in the pull request: https://github.com/apache/spark/pull/13076#discussion_r63142140 --- Diff: mllib/src/main/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifier.scala --- @@ -65,22 +63,23 @@ private[ml] trait MultilayerPerceptronParams extends PredictorParams "it is adjusted to the size of this data. Recommended size is between 10 and 1000", ParamValidators.gt(0)) - /** @group getParam */ + /** @group expertGetParam */ final def getBlockSize: Int = $(blockSize) /** - * Allows setting the solver: minibatch gradient descent (gd) or l-bfgs. - * l-bfgs is the default one. + * The solver algorithm for optimization. + * Supported options: "gd" (minibatch gradient descent) or "l-bfgs". + * Default: "l-bfgs" * * @group expertParam */ final val solver: Param[String] = new Param[String](this, "solver", - " Allows setting the solver: minibatch gradient descent (gd) or l-bfgs. " + - " l-bfgs is the default one.", - ParamValidators.inArray[String](Array("gd", "l-bfgs"))) + "The solver algorithm for optimization. Supported options: " + + s"${MultilayerPerceptronClassifier.supportedSolvers.mkString(", ")}. (Default l-bfgs)", + ParamValidators.inArray[String](MultilayerPerceptronClassifier.supportedSolvers)) - /** @group getParam */ - final def getOptimizer: String = $(solver) + /** @group expertGetParam */ + final def getSolver: String = $(solver) /** * Model weights. Can be returned either after training or after explicit setting --- End diff -- See my comment [here](https://github.com/apache/spark/pull/12943/files/7cc27e91a9cfd234268c0b3bb3e05c22dddb8ce0#r62917637). I think this doc can be improved to indicate this can set the weights for initializing training, or explicitly set (and override) the weights on a trained model.
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