EXPLAINABLE AI IN GRADIENT BOOSTING ALGORITHM FOR PHISHING WEBSITE DETECTION
As the demand for optimal AI performance has grown, complex models have been developed, leading to a lack of transparency in explaining prediction outcomes. In recent years, three complex gradient boosting methods based on decision trees, namely XGBoost, CatBoost, and LightGBM, have been proposed...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/78308 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
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