Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/1290#issuecomment-53034921
[QA tests have
finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/19078/consoleFull)
for PR 1290 at commit
[`a1b6a7f`](https://github.com/apache/spark/commit/a1b6a7fd56fe4c687d237f560991e228e448a072).
* 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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