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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