TY - JOUR AU - Biem, Alain AU - Butrico, Maria AU - Feblowitz, Mark AU - Klinger, Tim AU - Malitsky, Yuri AU - Ng, Kenney AU - Perer, Adam AU - Reddy, Chandra AU - Riabov, Anton AU - Samulowitz, Horst AU - Sow, Daby AU - Tesauro, Gerald AU - Turaga, Deepak PY - 2015/03/04 Y2 - 2024/03/28 TI - Towards Cognitive Automation of Data Science JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 29 IS - 1 SE - Demonstrations DO - 10.1609/aaai.v29i1.9281 UR - https://ojs.aaai.org/index.php/AAAI/article/view/9281 SP - AB - <p> A Data Scientist typically performs a number of tedious and time-consuming steps to derive insight from a raw data set. The process usually starts with data ingestion, cleaning, and transformation (e.g. outlier removal, missing value imputation), then proceeds to model building, and finally a presentation of predictions that align with the end-users objectives and preferences. It is a long, complex, and sometimes artful process requiring substantial time and effort, especially because of the combinatorial explosion in choices of algorithms (and platforms), their parameters, and their compositions. Tools that can help automate steps in this process have the potential to accelerate the time-to-delivery of useful results, expand the reach of data science to non-experts, and offer a more systematic exploration of the available options. This work presents a step towards this goal. </p> ER -