AutoMLk: automated machine learning toolkit¶
This toolkit is designed to be integrated within a python project, but also independently through the interface of the app.
The framework is built with principles from auto-sklearn, with the following improvements:
- web interface (flask) to review the datasets, the search results and graphs
- include sklearn models, but also Xgboost, LightGBM, CatBoost and keras Neural Networks
- 2nd level ensembling with model selection and stacking
- can be used in competition mode (to generate a submit file from a test set), on benchmark mode (separate train set and public set) and standard mode.
We have provided some public datasets to initialize the framework and compare results with best scores.