[R] Categorical Variables and Machine Learning

[Lorenzo Isella]

Dear All,
Please consider a dataframe like the one below (I am showing only a few 
rows).

>          role degree strength weight count disparity intermittency
>            P     10       82  18017     2  2.317073  5.550314e-05
>            P      7      529   4345    60  5.178466  6.904488e-03
>            P      8      609   4382    10  6.204535  1.141031e-03
>            D     42      230   6910    88  1.791153  6.367583e-03

You have a categorical variable (the role variable) which can assume 
only a few values ("P","D","C","N","A") referring to different 
individuals for whom you collect some extra properties (namely, degree, 
strength, weight, disparity and intermittency, like in the table above).
My goal is to find the most suitable property (or combination of 
properties) to guess the role of an individual. It looks like a typical 
machine learning problem, but I have categorical variables to predict.
I am drowning in the wealth of R packages for machine learning, but I 
really would like something simple and easy to use (consider that the 
dataset covers only 120 individuals, so performance is not a problem).
Any suggestion is appreciated.
Cheers

Lorenzo