https://github.com/mhmudfzli/loan-approval-prediction

This project demonstrates a comprehensive approach to solving a regression problem using various machine learning models. The notebook includes: Data Preprocessing, Exploratory Data Analysis (EDA), Model Training, Hyperparameter Tuning, Model Evaluation, Feature Importance
https://github.com/mhmudfzli/loan-approval-prediction

automl catboost numpy pandas python scikit-learn seaborn

Last synced: 4 months ago
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This project demonstrates a comprehensive approach to solving a regression problem using various machine learning models. The notebook includes: Data Preprocessing, Exploratory Data Analysis (EDA), Model Training, Hyperparameter Tuning, Model Evaluation, Feature Importance

• Host: GitHub
• URL: https://github.com/mhmudfzli/loan-approval-prediction
• Owner: MhmudFzli
• License: apache-2.0
• Created: 2025-01-18T15:17:03.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-01-18T15:26:37.000Z (over 1 year ago)
• Last Synced: 2025-01-18T16:30:33.268Z (over 1 year ago)
• Topics: automl, catboost, numpy, pandas, python, scikit-learn, seaborn
• Language: Jupyter Notebook
• Homepage:
• Size: 666 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Loan Approval Prediction

Goal: The goal for this competition is to predict whether an applicant is approved for a loan.

#### Here are the Steps wee took for the project:

1. Load and Concat Original with Competition Dataset

2. EDA

3. Preprocess

4. Train

#### Results:

* !BEST MODEL: Train Catboost Model with LGBM (blend-lasso):

![image](https://github.com/user-attachments/assets/61e8304a-0b19-4200-964c-7fe1cc2f15d1)

* AutoGloun:

![image](https://github.com/user-attachments/assets/57d63dbe-7d82-453c-bf7b-4bc8fac45b1c)

### Leaderboard (top 11%!):

![image](https://github.com/user-attachments/assets/8908ca25-9692-4fa1-9d99-b9f740a2f9fa)