On Dec 12, 2007 3:05 PM, Jason House <[EMAIL PROTECTED]> wrote: > > > On Dec 12, 2007 2:59 PM, Rémi Coulom <[EMAIL PROTECTED]> wrote: > > > > Do you mean a plot of the prediction rate with only the > > > gamma of interest varying? > > > > No the prediction rate, but the probability of the training data. More > > precisely, the logarithm of that probability. > > > I still don't know what you mean by this. >
He probably should use the word "likelihood" instead of "probability". http://en.wikipedia.org/wiki/Likelihood_function > > > > > If you have P(x)=A*exp(-x²/2sigma²), then log(P(x))=log(A)-x²/2sigma², > > and d²(log(P(x)))/dx²=-1/sigma². This means that, for a Gaussian > > probability distribution, the second-order derivative directly gives the > > variance. For distributions that look similar to a Gaussian, the > > second-order derivative is a good approximation. > > > This part I understand > > _______________________________________________ > computer-go mailing list > computer-go@computer-go.org > http://www.computer-go.org/mailman/listinfo/computer-go/ >
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