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RWNN (version 0.4)

Random Weight Neural Networks

Description

Creation, estimation, and prediction of random weight neural networks (RWNN), Schmidt et al. (1992) , including popular variants like extreme learning machines, Huang et al. (2006) , sparse RWNN, Zhang et al. (2019) , and deep RWNN, Henríquez et al. (2018) . It further allows for the creation of ensemble RWNNs like bagging RWNN, Sui et al. (2021) , boosting RWNN, stacking RWNN, and ensemble deep RWNN, Shi et al. (2021) .

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Version

Install

install.packages('RWNN')

Monthly Downloads

119

Version

0.4

License

MIT + file LICENSE

Maintainer

Sc3<b8>ren Vilsen

Last Published

September 3rd, 2024

Functions in RWNN (0.4)

rwnn

Random weight neural networks
reduce_network

Reduce the weights of a random weight neural network.
classify

Classifier
RWNN-object

An RWNN-object
RWNN-package

RWNN: Random Weight Neural Networks
ERWNN-object

An ERWNN-object
boost_rwnn

Boosting random weight neural networks
control_rwnn

rwnn control function
ae_rwnn

Auto-encoder pre-trained random weight neural networks
bag_rwnn

Bagging random weight neural networks
ed_rwnn

Ensemble deep random weight neural networks
predict.RWNN

Predicting targets of an RWNN-object
predict.ERWNN

Predicting targets of an ERWNN-object
stack_rwnn

Stacking random weight neural networks
example_data

Example data