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The main purpose of our project is to apply Genetic algorithms to search optimal hyper-parameters of machine learning algorithms and data argumentation algorithms as well as the suitable number of features.
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Our project includes the following contents:
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Using a dataset about "Predict student dropout and academic success" to build prediction models. Link dataset: https://www.kaggle.com/datasets/thedevastator/higher-education-predictors-of-student-retention
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Handling Imbalanced Dataset by oversampling with SMOTE.
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Applying feature selection by using Kendall's tau.
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Optimizing parameters of machine learning algorithms (Decision tree, SVM, KNN) using CMA-ES approach.
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Evaluating the results after using the above methods with the dataset.
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🚩Dataset: Dataset
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🚩Source Code: Code
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📝Details Report: Report
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📝Slides Report: Slides
| STT | Họ và tên | MSSV | |
|---|---|---|---|
| 1 | Phạm Thiện Bảo | 20521107 | 20521107@gm.uit.edu.vn |
| 2 | Nguyễn Huỳnh Hải Đăng | 20521159 | dnng2002@gmail.com |
| 3 | Phan Huy Mạnh | 19521828 | 19521828@gm.uit.edu.vn |