Fixes and improvements from code review #23
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- Corrected a typo in README.md ('suach' to 'such').
- Verified that the model training script (`Diabetes Predictor - Deployment.py`) uses the correct train/test split variables. Noted that the model .pkl file cannot be regenerated without the original `kaggle_diabetes.csv` dataset.
- Fixed a typo in a code comment in `app.py` ('CLassifier' to 'Classifier').
- Added `test_app.py` with a unit test for the `/predict` API endpoint. The test is correctly implemented but currently fails due to `ModuleNotFoundError: No module named 'sklearn.ensemble.forest'`. This indicates the `diabetes-prediction-rfc-model.pkl` was created with an older, incompatible version of scikit-learn. The test file is included for future use should the model be updated or the environment matched.
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Diabetes Predictor - Deployment.py) uses the correct train/test split variables. Noted that the model .pkl file cannot be regenerated without the originalkaggle_diabetes.csvdataset.app.py('CLassifier' to 'Classifier').test_app.pywith a unit test for the/predictAPI endpoint. The test is correctly implemented but currently fails due toModuleNotFoundError: No module named 'sklearn.ensemble.forest'. This indicates thediabetes-prediction-rfc-model.pklwas created with an older, incompatible version of scikit-learn. The test file is included for future use should the model be updated or the environment matched.