Artificial Neural Network Model Builder

This MATLAB program offers exceptional flexibility for building artificial neural network models, enabling users to freely configure the number of layers and units per layer according to their specific requirements. By adjusting these architectural parameters, you can create tailored neural networks optimized for various problems and datasets. The implementation supports common network architectures through MATLAB's Neural Network Toolbox functions like 'feedforwardnet' for multilayer perceptrons or 'patternnet' for classification tasks. Whether tackling classification, regression, or other machine learning challenges, this program provides the necessary infrastructure. Beyond model construction, it includes comprehensive functions for network training (using algorithms like Levenberg-Marquardt backpropagation 'trainlm' or scaled conjugate gradient 'trainscg') and optimization techniques to enhance model performance. Key features include customizable training parameters (learning rate, epochs, error goals) and validation methods to prevent overfitting. Thus, users can efficiently build sophisticated neural network architectures to address diverse computational problems while leveraging MATLAB's built-in visualization tools for analyzing network performance and training progress.