Metadata-Version: 2.1
Name: loan_amount_model_package
Version: 0.0.4
Summary: A package to estimate loan amount suitable for a customer
Author: chibuikeeugene
Author-email: chibuikeeugene@gmail.com
Requires-Python: >=3.9,<4.0
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: feature-engine (>=1.8.0,<2.0.0)
Requires-Dist: hyperopt (>=0.2.7,<0.3.0)
Requires-Dist: ipykernel (>=6.29.4,<7.0.0)
Requires-Dist: joblib (>=1.4.2,<2.0.0)
Requires-Dist: loguru (>=0.7.2,<0.8.0)
Requires-Dist: mlflow (>=2.13.2,<3.0.0)
Requires-Dist: numpy (>=1.26.4,<2.0.0)
Requires-Dist: pandas (>=2.2.2,<3.0.0)
Requires-Dist: pydantic (>=2.7.3,<3.0.0)
Requires-Dist: scikit-learn (>=1.5.0,<2.0.0)
Requires-Dist: scipy (>=1.13.1,<2.0.0)
Requires-Dist: strictyaml (>=1.7.3,<2.0.0)
Description-Content-Type: text/markdown

# LOAN AMOUNT PREDICTION  

A machine learning program that estimates the amount of loan to be issued as seen in the dataset given. This program uses a **simple linear lassocv algorithm** to estimate the likely loan user should be eligible for.  

## Data set and its description  

| Data              | Description                            |
|-------------------|----------------------------------------|
| Loan_ID           | Unique loan request identifier         |
| Gender            | sex of the user                        |
| Married           | Marital status                         |
| Dependents        | Number of dependents                   |
| Education         | if the candidate is graduate or not    |
| Self_Employed     | if the user is working for himself     |
| ApplicantIncome   | total income of the candidate          |
| CoapplicantIncome | total income of the borrower's partner |
| LoanAmount        | Amount requested                       |
| Loan_Amount_Term  | in months                              |
| Credit_History    | 1(okay or eligible), 0(Not eligible)   |
| Property_Area     | nature of where the borrower live      |
| Loan_Status       | if loan was granted or not             |

## Dependencies and packages  

1. python = "^3.9"
2. numpy = "^1.26.4"
3. pandas = "^2.2.2"
4. pydantic = "^2.7.3"
5. scikit-learn = "^1.5.0"
6. strictyaml = "^1.7.3"
7. feature-engine = "^1.8.0"
8. joblib = "^1.4.2"
9. mlflow = "^2.13.2"
10. ipykernel = "^6.29.4"
11. hyperopt = "^0.2.7"
12. scipy = "^1.13.1"
13. loguru = "^0.7.2"

## Source code link  

Source code link:
[Github link](https://github.com/chibuikeeugene/loan-amount-prediction.git)
