https://github.com/cran/automl
Tip revision: 793e489bc1062a8b0b7fa8d1030c80557a657875 authored by Alex Boulangé on 27 January 2019, 14:50:03 UTC
version 1.2.7
version 1.2.7
Tip revision: 793e489
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)