Package: deepnet 0.2.1
deepnet: Deep Learning Toolkit in R
Implement some deep learning architectures and neural network algorithms, including BP,RBM,DBN,Deep autoencoder and so on.
Authors:
deepnet_0.2.1.tar.gz
deepnet_0.2.1.zip(r-4.7)deepnet_0.2.1.zip(r-4.6)deepnet_0.2.1.zip(r-4.5)
deepnet_0.2.1.tgz(r-4.6-any)deepnet_0.2.1.tgz(r-4.5-any)
deepnet_0.2.1.tar.gz(r-4.7-any)deepnet_0.2.1.tar.gz(r-4.6-any)
deepnet_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
deepnet/json (API)
| # Install 'deepnet' in R: |
| install.packages('deepnet', repos = c('https://runxiao.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:6e1efd18ae. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 100 | ||
| source / vignettes | OK | 121 | ||
| linux-release-x86_64 | OK | 101 | ||
| macos-release-arm64 | OK | 137 | ||
| macos-oldrel-arm64 | OK | 129 | ||
| windows-devel | OK | 64 | ||
| windows-release | OK | 69 | ||
| windows-oldrel | OK | 99 | ||
| wasm-release | OK | 79 |
Exports:dbn.dnn.trainload.mnistnn.predictnn.testnn.trainrbm.downrbm.trainrbm.upsae.dnn.train
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Training a Deep neural network with weights initialized by DBN | dbn.dnn.train |
| Load MNIST DataSet | load.mnist |
| Predict new samples by Trainded NN | nn.predict |
| Test new samples by Trainded NN | nn.test |
| Training Neural Network | nn.train |
| Generate visible vector by hidden units states | rbm.down |
| Training a RBM(restricted Boltzmann Machine) | rbm.train |
| Infer hidden units state by visible units | rbm.up |
| Training a Deep neural network with weights initialized by Stacked AutoEncoder | sae.dnn.train |
