On Dec 12, 2007 3:09 PM, Álvaro Begué <[EMAIL PROTECTED]> wrote: > > > 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 >
Clearly I'm missing something, because I still don't understand. Let's take a simple example of a move is on the 3rd line and has a gamma value of 1.75. What is the equation or sequence of discrete values that I can take the derivative of? Doing conditional probabilities based on "move is on 3rd line" and "move is selected" (AKA pure training data) seems to yield a fixed value rather than something approximating a normal distribution.
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