A problem containing experimental data obtaining by comparing several instances of Machine Algorithms from the Weka library. The variables are as follows:
A data frame with
method. Classification algorithms used in the experimen (NaiveBayes, J48, IBk)
problem. Problems used as benchmark in the comparison, up to 12.
featureSelection. Boolean parameter indicating if the data was preprocessed
fold. For each configuration a 10-fold cross validation was performed. This variable is a numeric value ranging from 1 to 10.
accuracy. This is a measure of the performance of each algorithm. Representing the percentage of correctly classified instances.
trainingTime. A second measure of performance. This one indicates the time in seconds that took the algorithm to build the model.
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