Must-See: Why “three principles”? Why not “five principles”?

Bin Yu: Three principles for data science: predictability, stability, and computability: “September 12, 2017 :: 4:10pm to 5:00pm :: 190 Doe Library” https://bids.berkeley.edu/events/three-principles-data-science-predictability-stability-and-computability

Bin Yu: Three principles for data science: predictability, stability, and computability: “Prediction is a useful way to check with reality… http://delivery.acm.org/10.1145/3110000/3105808/p5-yu.pdf?

…Good prediction implicitly assumes stability between past and future. Stability (relative to data and model perturbations) is also a minimum requirement for interpretability and reproducibility of data driven results (cf. Yu, 2013). It is closely related to uncertainty assessment. Obviously, both prediction and stability principles cannot be employed without feasible computational algorithms, hence the importance of computability

https://www.youtube.com/watch?v=xqBW8QKs9q4