Comprehensive Loan Information for Credit Risk Analysis

[abhisheks008]

ML-Crate Repository (Proposing new issue)

🔴 Project Title : Comprehensive Loan Information for Credit Risk Analysis
🔴 Aim : The aim of this project is to analyze the information for credit risk based oon the given data.
🔴 Dataset : https://www.kaggle.com/datasets/nezukokamaado/auto-loan-dataset
🔴 Approach : Try to use 3-4 algorithms to implement the models and compare all the algorithms to find out the best fitted algorithm for the model by checking the accuracy scores. Also do not forget to do a exploratory data analysis before creating any model.

---

📍 Follow the Guidelines to Contribute in the Project :

• You need to create a separate folder named as the Project Title.
• Inside that folder, there will be four main components.
  • Images - To store the required images.
  • Dataset - To store the dataset or, information/source about the dataset.
  • Model - To store the machine learning model you've created using the dataset.
  • requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
• Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.

---

🔴🟡 Points to Note :

• The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
• "Issue Title" and "PR Title should be the same. Include issue number along with it.
• Follow Contributing Guidelines & Code of Conduct before start Contributing.

---

✅ To be Mentioned while taking the issue :

• Full name :
• GitHub Profile Link :
• Participant ID (If not, then put NA) :
• Approach for this Project :
• What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.)

---

Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

[hemant933]

Full name : Hemant chaudhary
GitHub Profile Link : github.com/hemant933
Participant ID (If not, then put NA) :
Approach for this Project : i will use vectorization and pipeline to analyse the data and then apply model
What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.) IWOC24

[abhisheks008]

Can you share more about the approach, it's not clear to me.

[avrk18]

Full Name : Aditya Vema Reddy Kesari
GitHub profile link : github.com/avrk18
Participant ID (If not, then put NA) : NA
Approach for this Project : I will use feature selection techniques such as fisher_score for numeric columns and chi2 values for categorical columns and then use decision trees to find feature importance. Depending on their importance we can construct new features as well if required. After bucketing and/or scaling for numeric columns, I will explore 3-4 algorithms and judge their accuracy.
What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.) JWOC 24

[abhisheks008]

Assigned to @avrk18 under JWOC.

[PranavJha2k3]

Full name : Pranav Jha
GitHub Profile Link : https://github.com/PranavJha2k3
Participant ID (If not, then put NA) : NA
Approach for this Project : Will perform EDA and other ML models (Logistic regression , Decision tree , Random forrest) and compare their F1 score , accuracy and other metrics to find the best fit
What is your participant role? SSOC, 2024
@admin Please assign me this issue!

[abhisheks008]

Implement 5-6 models for this project.
Assigned @PranavJha2k3