Using various supervised learning estimators in Sci-Kit Learn to get the best prediction accuracy if possible for the pima indians dataset.
Begin by reviewing the package requirements in requirements.txt
Train - test split accuracy with SVM(Support Vector Classifier) 0.77
Train - test split accuracy with Random Forest Classifier 0.76
Accuracy mean cross-validation score: 0.83 scoring "roc_auc" for Random forest Classifier Accuracy mean cross-validation score: 0.69 scoring "roc_auc" for Support Vector Classfier
Original Owners:
National Institute of Diabetes and Digestive and Kidney Diseases
Build docker image
docker build -t pimaMLsklearn .Run the Docker image
docker run -it -p 9999:9999 pimaMLsklearn:latest