The data science machine : emulating human intelligence in data science endeavors

Abstract

Data scientists are responsible for many tasks in the data analysis process including formulating the question, generating features, building a model, and disseminating the results. The Data Science Machine is a automated system that emulates a human data scientist's ability to generate predictive models from raw data. In this thesis, we propose the Deep Feature Synthesis algorithm for automatically generating features for relational datasets. We implement this algorithm and test it on 3 data science competitions that have participation from nearly 1000 data science enthusiasts. In 2 of the 3 competitions we beat a majority of competitors, and in the third, we achieve 94% of the best competitor's score. Finally, we take steps towards incorporating the Data Science Machine into the data science process by implementing and evaluating an interface for users to interact with the Data Science Machine.