Basic implementation of different classifiers for predicting whether a patient has diabetes or not. This is simple binary classification based on the pima-indian-diabetes-dataset found on Kaggle.
Experimented with the following classifiers:
- SVM
- Random Forest
- Logistic Regression
- Naive Bayes
- Ada Boost
- Ensemble Classifier
Also played around cleaning and standardizing the dataset.
- python-2.7.11
- scikit-learn
- Clone the repository
- Change the parameters of
Grid-Search(optional) - Run the file corresponding to the classifier you want.
eg
python svm.py