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From loachli <>
Subject [GitHub] spark pull request: [MLLIB] [spark-2352] Implementation of an Arti...
Date Mon, 22 Dec 2014 08:17:20 GMT
Github user loachli commented on the pull request:
    @avulanov: *Could you write a brief description to the ANN test called "Gradient of ANN"
to let the reader understand more clearly what we are testing?*
    The test ensures that the ANNLeastSquaresGradient is correctly implemented.
    It does so by comparing the computation of the gradient in the ANNLeastSquaresGradient
class with an approximation of the gradient. If we denote the squared error of the neural
network with E(w, x), where w=(w_ijl) is the weights vector, ANNLeastSquaresGradient.compute
calculates the gradient dE(w_ijl, x)/dw_ijl. This gradient is subsequently compared with the
    (E(w_ijl + eps, x) - E(w_ijl)) / eps
    for all weights w_ijl. For eps we chose the value 1e-6.
    If the difference is not too big (less than "accept=1e-7"), the ANNLeastSquaresGradient.compute
function is supposed to be correctly implemented.
    Maybe we should add some comments in the code about this.

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