API for EdwinGraham/EdNet
Train deep neural networks for classification and regression
| Global functions | |
|---|---|
| EdNetTrain | Man page Source code |
| backwardPropagation | Source code |
| computeCost | Source code |
| costBernoulli | Source code |
| costCategorical | Source code |
| costGamma | Source code |
| costNormal | Source code |
| costPoisson | Source code |
| costTweedie | Source code |
| devianceBernoulli | Man page Source code |
| devianceCategorical | Man page Source code |
| devianceGamma | Man page Source code |
| devianceNormal | Man page Source code |
| deviancePoisson | Man page Source code |
| devianceTweedie | Man page Source code |
| dfBinary | Man page |
| dfGamma | Man page |
| dfPoisson | Man page |
| dfTweedie | Man page |
| forwardPropagation | Source code |
| generateMiniBatches | Source code |
| gradGamma | Source code |
| gradGeneric | Source code |
| gradTweedie | Source code |
| initialiseParams | Source code |
| initialise_s | Source code |
| initialise_v | Source code |
| normalise | Man page Source code |
| onehotEncode | Man page Source code |
| outputFamily | Source code |
| predict.EdNetModel | Man page Source code |
| predictedClass | Man page Source code |
| relu | Man page Source code |
| sigmoid | Man page Source code |
| softmax | Source code |
| updateParameters | Source code |
| weightedMean | Source code |
