xert wrote:
We have not disclosed the details of our methods but we've been very open on the principles on which they work...
It's not "AI" or "ML" in the sense of, say, an NN....
We make no claims on the accuracy of the prediction model and rely on our users to judge for themselves how well it works for them....
I do look forward to seeing more on your NN implementation. We are looking at NN in combination with our models to bring applications to a broader range of sports and activities.
Thanks Armando,
I appreciate your honesty (and support!)
FWIW, for others reading, I have no problem with 'if-then rules' systems so long as they're advertised as such and not as "A.I." If athletes know who is writing the rules for the system they're in a better place to judge the worth of the system, especially in the absence of a loss function that quantifies the true predictive accuracy/value of the system.
That said, using a model that quantifies its true predictive accuracy is, obviously, always the better way to go.
Best,
Alan Couzens, M.Sc. (Sports Science)
Exercise Physiologist/Coach
Twitter: https://twitter.com/Alan_Couzens
Web: https://alancouzens.com
Last edited by:
Alan Couzens: Jan 15, 19 14:55