Man pages for Greg-Hallenbeck/easy.mlp
Easy-To-Use Multilayer Perceptron
| cce.loss | Categorical Cross-Entropy Loss function, used for... |
| create.mlp | Initialize a Neural Network. |
| forward.prop | Performs forward propagation through the neural network Most... |
| .ipynb_checkpoints/create.mlp-checkpoint | Initializes a new neural network. |
| leaky.relu | A "leaky" RELU function, and derivative. The slope in the... |
| linear | A linear activation function, and its derivative. |
| logit.loss | A Logistic Loss function, used for binary classification... |
| mse.loss | A Mean Squared Error Loss function, used for regression... |
| plot.mlp | Plot the Loss or Other Metrics of a Neural Network |
| predict.mlp | Make predictions using the neural network. |
| relu | A rectified linear unit or RELU = max(0, x) function, and its... |
| sigmoid | A sigmoid (= logistic) function, and its derivative. |
| softmax | A softmax activation, used for classifier networks as the... |
| split.dataset | Split a dataset into a design (X) matrix and labels (Y), and... |
| tanh | A hyperbolic tangent function, and its derivative. |
| train | Train a Neural Network |
