@@ -720,8 +720,9 @@ setMethod("predict", signature(object = "MultilayerPerceptronClassificationModel
720720# Returns the summary of a Multilayer Perceptron Classification Model produced by \code{spark.mlp}
721721
722722# ' @param object a Multilayer Perceptron Classification Model fitted by \code{spark.mlp}
723- # ' @return \code{summary} returns a list containing \code{layers}, the label distribution, and
724- # ' \code{tables}, conditional probabilities given the target label.
723+ # ' @return \code{summary} returns a list containing \code{labelCount}, \code{layers}, and
724+ # ' \code{weights}. For \code{weights}, it is a numeric vector with length equal to
725+ # ' the expected given the architecture (i.e., for 8-10-2 network, 100 connection weights).
725726# ' @rdname spark.mlp
726727# ' @export
727728# ' @aliases summary,MultilayerPerceptronClassificationModel-method
@@ -732,7 +733,6 @@ setMethod("summary", signature(object = "MultilayerPerceptronClassificationModel
732733 labelCount <- callJMethod(jobj , " labelCount" )
733734 layers <- unlist(callJMethod(jobj , " layers" ))
734735 weights <- callJMethod(jobj , " weights" )
735- weights <- matrix (weights , nrow = length(weights ))
736736 list (labelCount = labelCount , layers = layers , weights = weights )
737737 })
738738
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