Hi all,
I am working with several algorithms in order to classify crops from
information given into each plot/parcel. I am using 4 methods: *(1)*
BayesNaives, *(2)* AdaBoostM1 (with J48), *(3)* RandomForest and *(4)* SMO
(with kernel=PolyKernel).
I want, not only the class for each instance but also its probability for
each class. It can be done via command line adding "-distribution". It adds
the probability matrix to the output so you have the probability for every
class and for each instance.
However, I have not been able to find how each of the mentioned methods
calculates these probabilites.
If I am right,
-*/Bayes Naives/* has the probability implicit in its calculation.
-*/SMO /*takes the distance to the hyperplane that divides the classes and
fits a logisitic (sigmoid) function, so the given "distribution" are those
values rather than real probabilities.
-In */Random Forest/*, intuitively, but not sure, I understand that, given
100 trees, the distribution of probabilities are obtained from the times a
class is voted from each tree and for each instance.
-In the case of */AdaBoost/*, no idea.
Any correction, explanation (intuitive and/or mathematical) with be more
than welcome.
Thanks you all in advance,
Jaime
Jaime
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