Integrating "two Cultures" in Data Science: Predictability, Computability, and Stability (PCS)

• Activity Number: 385 - Leo Breiman Award
• Type: Invited
• Date/Time: Tuesday, July 30, 2019 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistical Learning and Data Science
• Author(s): Bin Yu*
• Companies: UC Berkeley
• Keywords: Predictability; computability; stability; machine learning; inference; data science life cycle

Abstract

In this talk, I'd like to discuss the intertwining importance and connections of three principles of data science: predictability, computability and stability (PCS). The related PCS workflow builds on machine learning, expands statistical inference, and covers the data science life cycle. It requires transparent documentation of narratives and codes. The three principles will be demonstrated in the context of two collaborative projects in neuroscience and genomics for interpretable data results and testable hypothesis generation.