Hello,
the answer of Vijay's question would be insteresting to me too, since I
should use OnlineLogisticRegression in order to calculate probabilities
(as far as I see, there are no probability calculation functions in
AdaptiveLogisticRegression). So, for example, how to determine 'number
of features' ? In the 'donut' example, 'number of features' is set to
20, but where does this 20 come from ?
Thanks.
Svetlomir.
Am 04.07.2011 19:30, schrieb Vijay Santhanam:
Hi,
I'm trying to model the following training data that's targeting the gender
and from what I've been reading in the archives of the mailing list, the
OnlineLogisticRegression classifier is the easiest to get up and running..
sex height (feet) weight (lbs) foot size(inches) male 6 180 12 male 5.92
(5'11") 190 11 male 5.58 (5'7") 170 12 male 5.92 (5'11") 165 10 female
5 1006female5.5 (5'6")1508female5.42 (5'5")1307female5.75 (5'9")1509
But, I don't know what process to adopt that will allow me to fine tune the
parameters of the learner so it will pick the following as female..
sex height (feet) weight (lbs) foot size(inches) sample 6 130 8
I'm just guessing parameters at the moment. Does anyone have any advice for
fine tuning the learner for these parameters?
I'd really appreciate some guidance or general advice about how to approach
a problem like this, or which algorithm to use.
Thanks,
V
