A python notebook used to automate the process of looking for the best initial classification machine learning model.
This notebook will consist of a main function diagnose(), which takes X: a numeric values only DataFrame which has features, and y: a numeric values only DataFrame which has labels, and returns a DataFrame showing scores of trained models sorted descendingly.
This diagnosis will consist of these models:
- K Nearest Neighbour
- Logestic Regression
- Gaussian Naive Bays Classifier
- Decision Trees
- Boosted Trees
- Random Forest
- Support Vector Machine (rbf, linear, poly)