Man pages for dnn
Deep Neural Network Tools for Probability and Statistic Models
| activation | Activation function |
| bwdNN | Back propagation for dnn Models |
| deepAFT | Deep learning for the accelerated failure time (AFT) model |
| deepGLM | Deep learning for the generalized linear model |
| deepSurv | Deep learning for the Cox proportional hazards model |
| dnnControl | Auxiliary function for 'dnnFit' dnnFit |
| dnnFit | Fitting a Deep Learning model with a given loss function |
| dNNmodel | Specify a deep neural network model |
| dnn-package | An R package for the deep neural networks probability and... |
| fwdNN | Feed forward and back propagation for dnn Models |
| hyperTuning | A function for tuning of the hyper parameters |
| ibs.deepAFT | Calculate integrated Brier Score for deepAFT |
| mseIPCW | Mean Square Error (mse) for a survival Object |
| optimizerSGD | Functions to optimize the gradient descent of a cost function |
| plot | Plot methods in dnn package |
| predict.deepAFT | Predicted Values for a deepAFT Object |
| print a summary of fitted deep learning model object | |
| residuals.deepAFT | Calculate Residuals for a deepAFT Fit. |
| rSurv | The Survival Distribution |
| survfit.deepAFT | Compute a Survival Curve from a deepAFT or a deepSurv Model |
