This software make an extensive usage of the following packages that must be installed:
caret, randomForest, kernlab
You can install this packages inside an R-session with:
install.packages(c('caret', 'randomForest', 'kernlab'))
You can install the pratto package directly from your R session using the
install_github function from the
# Loading the ROGER library. library('ROGER') # Loading the data data('testset') # Let's see the structure of this dataset str(testset) # Let's keep only with the 'r' and 'v' columns that will be used to predict, and # save the real classification for future comparison. cat <- testset[, c(4,5)] real_class <- testset$flag1 # Let's predict the proabability of being of each class using our ML pred_prob <- get_class(cat, knn)
In the Examples section you can find more examples!
Héctor J. Martínez (IATE-OAC-UNC)
Valeria Coenda (IATE-OAC-UNC)
Hernán Muriel (IATE-OAC-UNC)
Andrés N. Ruiz (IATE-OAC-UNC)
Cristian Vega (CCT-UNLP)
Sofía Cora (CCT-UNLP)
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