Weighted Support Vector Machine Classification with Feature Reduction

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Resource Overview

MATLAB implementation of weighted support vector machine classification algorithm that effectively reduces feature dimensionality, includes sample datasets, requires CVX optimization toolbox for direct execution.

Detailed Documentation

This implementation employs a weighted support vector machine classification algorithm designed to reduce feature dimensionality while maintaining classification performance. The package includes sample datasets for immediate testing. After installing the CVX optimization toolbox, users can directly execute the MATLAB code which implements feature weighting through regularization parameters and kernel function modifications. The algorithm optimizes the margin classification boundary by assigning adaptive weights to different features, effectively suppressing irrelevant or redundant features during the training process. This approach enhances classification accuracy and computational efficiency by focusing on the most discriminative features.

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