Loan-Approval

Loan Approval Classification

Project is a Part of Hackathon by Analytics Vidhya.

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Evaluation Metric is Accuracy.

Data Sets : Train and Test Files from Analytics Vidhya Hackathon.

Data

Important Features for Loan Approval Prediction

1. Education : High Level of Education - High Chance of Loan Approval

2. Income of Applicant : High Income - High Chance of Loan Approval

3. Loan Amount : Low Loan Amount - High Chance of Loan Approval

4. Loan Term : Short Loan Term - High Chance of Loan Approval

5. Credit History : Good Credit Score - High Chance of Loan Approval

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Flow of Project :

1. Exploratory Data Analysis

2. Data Visualization

3. Data Preprocessing

4. Data Modelling and Evaluation

5. Conclusion

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Machine Learning Algorithms :

1. Logistic Regression

2. Decision Tree Classifier

3. Random Forest Classifier

4. XGBOOST Classifier

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Model Selection Technique :

1. Stratified K Fold

2. Grid Search Cross Validation

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Data Evaluation Techniques :

1. Confusion Matrix

2. ROC AUC Curve

3. Classification Report

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Topics you will Learn with this Project :

1. Univariate Analysis

2. Bivariate Analysis

3. Visualizations

4. Handling Missing Values

5. Outlier Treatment

6. Transformation

7. Feature Engineering and Dimensionality Reduction

8. Tuning Hyperparameters

9. Feature Importance

10. Improving Model

This Project is a Good Combination of Almost Every Important Concepts in Machine Learning.

Covering Every Aspects of Creating a Good Model.

Models

1. Decision Tree
2. Random Forest