5 ms·
Once ML models are routinely provided time-based features; particularly deltas between events and the 3rd derivative rate-of-change; they are going to identify
by matchagaucho 8y ago
Once ML models are routinely provided time-based features; particularly deltas between events and the 3rd derivative rate-of-change; they are going to identify some amazing causal relationships that humans are incapable of today.
- daveguy 8y agoWhy 3rd derivative? Do you think that because we don't typically work with 3rd derivatives to explain physical phenomenon that there is a lot we are missing? Or are there particular scenarios where you see 3rd derivative as being critical to causality? 1st derivative = direct causality, 2nd derivative = ability to affect change, 3rd derivative = ?? tertiary causes. Wait. Doesn't a derivative mathematically define a causal relationship? EDIT: nevermind re: derivative = causal ... that's just a correlation relationship. dx/dt. Still I'm curious as to what is special about the 3d derivative (besides jerk).
- scottlocklin 8y ago3rd derivative is a simple filter on acceleration. Obvious feature in something like fault prediction on heavy machinery. What you really want, though are the ability to decouple and infer relationships between short and long term features (something like the cepstrum transform from speech analysis).