Hello Ted,
what are the main issues of the probability estimations of the logistic
regression ? I am developing a medical application for making
probability estimations using time series and I that's why I would know
if they are critical for me.
Many thanks and best regards,
Svetlomir.
Am 15.06.2011 20:44, schrieb Ted Dunning:
This is what the term Naive is used in the name. The scores for this kind
of algorithm are 0 to 1 or are logarithms of such a number, but are not at
all calibrated probabilities.
And, frankly, it is rare in practice for the output of logistic regression
to be calibrated either. Those outputs are much more like probabilities,
but they still have some issues.
On Wed, Jun 15, 2011 at 6:56 PM, Svetlomir Kasabov<
skasa...@smail.inf.fh-brs.de> wrote:
unfortunately, Mahout's Naive Bayes implemention can't calculate
probabilities. You are now probably really astonished - I could'nt believe
it too, as I read that (I think this is some kind of 'strange', since
Bayes's main concept is probability calculation). It's a pitty, that such a
great framework like Mahout has restricted the Bayesian concept that way. In
addition, Naive Bayes is (as far as I know) only text-oriented, you can
apply it only on documents . Mahout is still wonderful, though, because it
lets us calculate probabilities using Logistic Regression.
