MODEL KLASIFIKASI GENETIC-XGBOOST DENGAN T-DISTRIBUTED STOCHASTIC NEIGHBOR EMBEDDING PADA PERAMALAN PASAR
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Extreme Gradient Boosting atau XGBoost merupakan metode ensemble boosting yang sangat populer dan berkinerja baik. Disisi lain XGBoost menerapkan sangat banyak parameter atau hyper parameter. Penentuan nilai secara manual tentu saja sangat sulit dan lama. Pada penelitian ini, Genetic Algoritm (GA) diterapkan untuk penelusuran nilai parameter XGBoost. Model XGBoost dievalusi dengan membandingkan ROC dengan beberapa model berbasis tree. Hasil pengujian ROC Genetic-XGBoost, Gradient Boost, dan Random Forest masing-masing sebesar 0, 987, 0,99, dan 0,957. Hasil ROC ke tiga model menunjukkan bahwa model Genetic-XGBoost memiliki performa yang lebih baik dari model-model lain.
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Referensi
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