# Car Evaluation
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Students: Nguyen Duy Tien, Chau Le Quan
Instructors: Huy Le, Ha V. Nguyen, Tung H. Cao, Hung Ngo
Mentor/Advisor: Ha V. Nguyen
Course: Machine Learning for AI, 2022
LeHongPhong Highschool for the Gifted, HCMC Vietnam
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## Task description $T$
<br>
- What does your system/application do? Classifying the acceptability of cars based on their features.
- What does it take as input? 6 attributes
- What does it give as output? The acceptability of cars as: unacc, acc, good, vgood
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## Experience $E$
<br>
- What is one training example $(\mathbf{x}, y)$?
- Where do the training data come from? How many examples?
- We get dataset from [`UCI Machine Learning Repository`](https://archive.ics.uci.edu/ml/datasets/car+evaluation) - Car Evaluation Data Set and [`Kaggle - Car Evaluation Dataset`](https://www.kaggle.com/code/mykeysid10/car-evaluation/data)
- 1728 samples
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## Performance metrics $P$
- Accuracy
- Precision
- Recall
- F1 score
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## Algorithm $A$ for training
<br>
Random Forest
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## Exploring Data and Choosing Model
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## Model Building and Building Web App
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## Deployment & Integration
<br>
* Push to github
* Deploy to heroku
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## Demonstrations
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Thank you for paying attention!
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