Built my own SVM classifier from scratch in Rust. It uses SMO optimization, have linear and rbf kernel, uses grid search to tune the hyperparameters.
I tested it on two datasets one using Linear dataset and other using RBF, these were the results:
| Dataset | Kernel | Accuracy | Recall | F1 |
|---|---|---|---|---|
| Banknote Auth | Linear | 96% | 94% | 95% |
| Breast Cancer | RBF | 93% | 100% | 92% |
The plot.rs file, used for plotting only was written using AI as I could not wrap my head around plotters crate, apart from that everything was by my own.
Repo Link: Github Repo
Happy to get some feedback!
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