automl v1.2.7

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Deep Learning with Metaheuristic

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.

Readme

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)

Functions in automl

Name Description
autopar parameters for automatic hyperparameters optimization
automl_predict automl_predict
automl_train automl_train
hpar Deep Neural Net parameters and hyperparameters
pso PSO parameters and hyperparameters
automl_train_manual automl_train_manual
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Vignettes of automl

Name
automl.Rmd
howto_automl.Rnw
imgperc001.png
imgperc002.png
imgperc003.png
imgperc004.png
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Details

Type Package
BugReports https://github.com/aboulaboul/automl/issues
URL https://aboulaboul.github.io/automl https://github.com/aboulaboul/automl
License GNU General Public License
Encoding UTF-8
LazyData TRUE
RoxygenNote 6.1.0
NeedsCompilation no
Packaged 2019-01-27 15:30:00 UTC; aboul
Repository CRAN
Date/Publication 2019-01-27 15:50:03 UTC
suggests datasets
imports parallel , stats , utils
Contributors

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