Optimizing SVM Parameters Using Genetic Algorithm (GA)

Enhancing SVM classification accuracy through GA-based parameter optimization with implementation approaches

Supervised Naive Bayes Classification Algorithm with Non-independent Features

A supervised naive Bayes classification algorithm accounting for feature dependencies. Implements parameter estimation, processes training and test datasets, and outputs classification results with accuracy metrics.

Iris Data Classification Using Backpropagation Neural Network

Implementation of BP neural network for iris data classification, where achieving over 99% classification accuracy is possible by appropriately adjusting training epochs and precision parameters through code optimization.