algorithms for model creation and observation of which of the
models performs best.
1) Training and Testing
The data set used for training is mainly a portion from the
dataset from which the classifying algorithm used learns the
class/result of the model created from each model, and the
four splits used in this study are shown in table 4. The
learning method is based on the attributes or features of the
dataset in comparison the result/class. And finally the output
is a model used to compare against the other half of the
dataset, which is the testing data