[mlpack-git] [mlpack] KathirvalavakumarSubavathi initialization test (#414)

Marcus Edel notifications at github.com
Sun Mar 1 11:03:38 EST 2015


T. Kathirvalavakumar and S. J. Subavathi proposed an efficient weight initialization method using Cauchy's inequality to improve the convergence in single hidden layer feed forward neural networks. We already implemented the algorithm, but there isn't a test which shows that the code works as expected. This is meant to fill this gap. The test case could compare the results given in the paper with our own implementation. Since we initialize the weights with uniformly distributed random numbers we have to run several iterations and compare the results with a small tolerance against the results from the paper.

For more information see:

* Thangairulappan Kathirvalavakumar, Subramanian Jeyaseeli Subavathi, "A New Weight Initialization Method Using Cauchy’s Inequality Based on Sensitivity Analysis", 2011

---
Reply to this email directly or view it on GitHub:
https://github.com/mlpack/mlpack/issues/414
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://mailman.cc.gatech.edu/pipermail/mlpack-git/attachments/20150301/f7c0ab31/attachment-0001.html>


More information about the mlpack-git mailing list