Forward Selection pada Support Vector Machine untuk Memprediksi Kanker Payudara
Sari
Kanker payudara merupakan masalah kesehatan yang serius, sehingga deteksi dini dari kanker payudara dapat berperan penting dalam perencanaan pengobatan. Pada penelitian ini Support Vector Machine dengan kernel (dot, polynomial, RBF) dan forward selection diterapkan. Perbandingan akurasi SVM tanpa forward selection dengan menggunakan forward selection menunjukkan selisih yang besar. Hasil penelitian menunjukkan SVM(RBF)+FS unggul dengan akurasi 85,38% dibandingkan dengan SVM(Polynomial & dot), selain itu SVM(RBF)+FS juga unggul dibandingkan algoritma machine learning lainnya dalam memprediksi dataset kanker payudara Coimbra.
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DOI: https://doi.org/10.31294/infortech.v1i2.7398
DOI (PDF): https://doi.org/10.31294/infortech.v1i2.7398.g3791
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