https://github.com/1adityakadam/multi-model-car-acceptability-classification

A Machine Learning Approach for Comparative Analysis of Logistic Regression, SVM, and Random Forest Techniques
https://github.com/1adityakadam/multi-model-car-acceptability-classification

ensemble-learning multinomial-logistic-regression random-forest svm-model

Last synced: 9 months ago
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A Machine Learning Approach for Comparative Analysis of Logistic Regression, SVM, and Random Forest Techniques

• Host: GitHub
• URL: https://github.com/1adityakadam/multi-model-car-acceptability-classification
• Owner: 1adityakadam
• Created: 2024-11-05T19:53:32.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-03-24T22:06:42.000Z (about 1 year ago)
• Last Synced: 2025-04-05T19:40:02.155Z (about 1 year ago)
• Topics: ensemble-learning, multinomial-logistic-regression, random-forest, svm-model
• Language: Jupyter Notebook
• Homepage:
• Size: 323 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          
Car Classification using Multiple Machine Learning Models

Car Classification dataset: 

https://www.kaggle.com/datasets/stealthtechnologies/car-evaluation-classification/code?datasetId=5908498&sortBy=dateRun&tab=profile&excludeNonAccessedDatasources=false

Applied models: 

- Multinomial Linear Regression, 

- SVM,

- Random Forest

- Ensemble



  Car Classification using Machine Learning Models Workbook




![image](https://github.com/user-attachments/assets/7073a760-8b66-4ed6-92a8-7b342add86a0) 

![image](https://github.com/user-attachments/assets/f34890b3-6bd2-4a54-a376-4ae4b0d730f2)

![image](https://github.com/user-attachments/assets/c9ecc288-7e4c-4573-9598-21d0acce8322)

![image](https://github.com/user-attachments/assets/83e78252-4b3f-4ad2-9c5b-9140ca5c33f0)