https://github.com/cran/automl
Revision dafc26a4ce301e9e934e5f3b8e5ac7e70fe971a3 authored by Alex Boulangé on 16 March 2019, 14:03:30 UTC, committed by cran-robot on 16 March 2019, 14:03:30 UTC
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Tip revision: dafc26a4ce301e9e934e5f3b8e5ac7e70fe971a3 authored by Alex Boulangé on 16 March 2019, 14:03:30 UTC
version 1.2.8
Tip revision: dafc26a
README.md
automl package fits from simple regression to highly customizable deep neural networks 
either with gradient descent or metaheuristic, using automatic hyper parameters 
tuning and custom cost function.
A mix inspired by the common tricks on Deep Learning and Particle Swarm Optimization.

(Key words: autoML, Deep Learning, Particle Swarm Optimization, learning rate, minibatch, 
batch normalization, lambda, RMSprop, momentum, adam optimization, learning rate decay, 
inverted dropout, particles number, kappa, regression, logistic regression)
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