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| import unittest | |
| import pandas as pd | |
| import numpy as np | |
| import os | |
| import sys | |
| # Add the src directory to the path | |
| sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) | |
| from src.models.loan_model import LoanApprovalModel | |
| class TestLoanModel(unittest.TestCase): | |
| def setUp(self): | |
| """Set up test fixtures""" | |
| self.model = LoanApprovalModel() | |
| # Create sample data | |
| self.sample_data = pd.DataFrame({ | |
| "income": [20000, 50000, 80000, 30000], | |
| "credit_score": [580, 720, 800, 650], | |
| "debt_to_income": [40, 25, 15, 30], | |
| "loan_amount": [150000, 200000, 300000, 180000], | |
| "loan_term": [30, 30, 15, 30], | |
| "employment_length": [2, 5, 10, 3], | |
| "home_ownership": ["RENT", "OWN", "OWN", "RENT"], | |
| "loan_purpose": ["HOME", "HOME", "HOME", "HOME"] | |
| }) | |
| def test_predict(self): | |
| """Test prediction functionality""" | |
| predictions = self.model.predict(self.sample_data) | |
| # Check that predictions are binary (0 or 1) | |
| self.assertTrue(all(pred in [0, 1] for pred in predictions)) | |
| # Check that higher income and credit score leads to approval | |
| self.assertEqual(predictions[2], 1, "High income and credit score should lead to approval") | |
| def test_predict_proba(self): | |
| """Test probability prediction functionality""" | |
| probabilities = self.model.predict_proba(self.sample_data) | |
| # Check that probabilities are between 0 and 1 | |
| self.assertTrue(all(0 <= prob[1] <= 1 for prob in probabilities)) | |
| # Check that probabilities are higher for better applications | |
| self.assertGreater(probabilities[1][1], probabilities[0][1], | |
| "Better application should have higher approval probability") | |
| def test_feature_importance(self): | |
| """Test feature importance functionality""" | |
| importance = self.model.feature_importance() | |
| # Check that feature importance is returned for all features | |
| self.assertEqual(len(importance), len(self.sample_data.columns)) | |
| # Check that importance values sum to approximately 1 | |
| self.assertAlmostEqual(sum(importance.values()), 1.0, places=5) | |
| if __name__ == "__main__": | |
| unittest.main() |