Package: RWNN 0.4

Søren B. Vilsen

RWNN: Random Weight Neural Networks

Creation, estimation, and prediction of random weight neural networks (RWNN), Schmidt et al. (1992) <doi:10.1109/ICPR.1992.201708>, including popular variants like extreme learning machines, Huang et al. (2006) <doi:10.1016/j.neucom.2005.12.126>, sparse RWNN, Zhang et al. (2019) <doi:10.1016/j.neunet.2019.01.007>, and deep RWNN, Henríquez et al. (2018) <doi:10.1109/IJCNN.2018.8489703>. It further allows for the creation of ensemble RWNNs like bagging RWNN, Sui et al. (2021) <doi:10.1109/ECCE47101.2021.9595113>, boosting RWNN, stacking RWNN, and ensemble deep RWNN, Shi et al. (2021) <doi:10.1016/j.patcog.2021.107978>.

Authors:Søren B. Vilsen [aut, cre]

# Install 'RWNN' in R:

install.packages('RWNN', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

Datasets:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

Last updated 2 months agofrom:731fbfcfd6. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Oct 04 2024
R-4.5-linux-x86_64	OK	Oct 04 2024

Help page	Topics
Auto-encoder pre-trained random weight neural networks	ae_rwnn ae_rwnn.formula
Bagging random weight neural networks	bag_rwnn bag_rwnn.formula
Boosting random weight neural networks	boost_rwnn boost_rwnn.formula
Classifier	classify
rwnn control function	control_rwnn
Ensemble deep random weight neural networks	ed_rwnn ed_rwnn.formula
An ERWNN-object	ERWNN-object
Example data	example_data
Predicting targets of an ERWNN-object	predict.ERWNN
Predicting targets of an RWNN-object	predict.RWNN
Reduce the weights of a random weight neural network.	reduce_network reduce_network.ERWNN reduce_network.RWNN
Random weight neural networks	rwnn rwnn.formula
An RWNN-object	RWNN-object
Stacking random weight neural networks	stack_rwnn stack_rwnn.formula