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implement a model to predict student success with Naive Bayes classifier

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Heewon-Hailey/Naive-Bayes-classifier

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Naïve Bayes classifier from scratch

About the project

This project aims to predict student success with Naive Bayes (NB) model.

The NB model and evaluating metrics are implemented from scratch. Also, it compares the difference between different splitting strategies (hold-out and cross-validation). It focuses on the implementation of the classifier based on its algorithm. Feature preprocessing and performance improvement are not considered.

Datasets

It includes 650 instances (students info.), each of which has 29 features and 1 label Grade.

school,sex,address,famsize,Pstatus,Medu,Fedu,Mjob,Fjob,reason,guardian,traveltime,studytime,failures,schoolsup,famsup,paid,activities,nursery,higher,internet,romantic,famrel,freetime,goout,Dalc,Walc,health,absences

Grade

🧑‍🎓 ➡️ 🅰️🅱️

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implement a model to predict student success with Naive Bayes classifier

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