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From SparkQA <>
Subject [GitHub] spark pull request: [MLLIB] [spark-2352] Implementation of an 1-hi...
Date Fri, 22 Aug 2014 08:47:33 GMT
Github user SparkQA commented on the pull request:
      [QA tests have finished](
for   PR 1290 at commit [`9bb9766`](
     * This patch **passes** unit tests.
     * This patch merges cleanly.
     * This patch adds the following public classes _(experimental)_:
      * `The 'ParallelANN' class is the main class of the ANN. This class uses a trait 'ANN',
which includes functions for calculating the hidden layer ('computeHidden') and calculation
of the output ('computeValues'). The output of 'computeHidden' includes the bias node in the
hidden layer, such that it does not need to handle the hidden bias node differently.`
      * `The input of the training function is an RDD with (input/output) training pairs,
each input and output being stored as a 'Vector'. The training function returns a variable
of from class 'ParallelANNModel', as described below.`
      * `The 'ParallelANN' class implements a Artificial Neural Network (ANN), using the stochastic
gradient descent method. It takes as input an RDD of input/output values of type 'Vector',
and returns an object of type 'ParallelANNModel' containing the parameters of the trained
ANN. The 'ParallelANNModel' object can also be used to calculate results after training.`
      * `abstract class GeneralizedSteepestDescentModel(val weights: Vector )`
      * `trait ANN `
      * `class LeastSquaresGradientANN(`
      * `class ANNUpdater extends Updater `

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