We trained 4 models viz. ‘KNN classifier model’, ‘Naive Bayes classifier model’, ‘Decision Tree classifier model’ and ‘Linear Regression classifier model’ for binary classification based on the attributes present in the dataset and predict whether a loan application should be approved or not.
| Accuracy Comparisons | Data with Null values | Data after processing Null values |
|---|---|---|
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- In this project we have a shortened ‘Predict Loan Application Status’ Dataset from Kaggle.
- In this dataset, the target attribute is the loan status which is in binary. So, we did a binary classification based on the attributes present in our dataset and predicted whether a loan application should be approved or not.
- We found out the score, classification report, plotted the Receiver Operating Characteristic graph and found out the Area Under Curve (AUC) for each of the models trained.
- We used the trained models to predict the outcomes using the given test dataset and compare the outcome of each model.
- We choose the best model based on the accuracy score and classification report.
- Detailed report is in the pdf file located here.
- Python - Python is an interpreted, object-oriented, high-level programming language with dynamic semantics
- NumPy - The fundamental package for scientific computing with Python
- SciPy - SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering
- pandas - pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
- matplotlib - Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
- seaborn - Seaborn is a Python data visualization library based on matplotlib.
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