Fortnet Recipes# Introduction Before You Start Where to start Basic Usage First Training with Fortnet First Predictions with Fortnet Incorporating External Atomic Features Fortformat Fnetdata: Generating a Dataset Fnetout: Extracting the Output Fortformat: Basic Fortnet IO Format Classes Behler-Parrinello-Neural-Network Atom-Centered Symmetry Functions Cross-Functional Settings Manual G-Function Specification Automatic Parameter Generation Atom-Specific Scaling Factors Activation Functions Hyperbolic Tangent Arcus Tangent Sigmoid SoftPlus Gaussian ReLU Leaky ReLU Bent Identity Heaviside Linear Loss Functions Mean Squared Error Root Mean Square Error Mean Absolute Error Mean Absolute Percentage Error Regularization Optimizer General Optimizer Settings Optimizer Specific Settings Analysis Calculating First Derivatives Interfaces with other codes Socket-Communication Atomic Simulation Environment - ASE Licence Bibliography
