After the first split, the decision tree algorithm examines each of the two subsets of data and finds a predictor variable and a value that gives the most information. ... Displaying the Decision Tree ...

The authors’ approach is based on differences between assembly op-code frequencies in malware and benign classes. They have also utilized decision tree algorithms to simplify the classification.

After training decision trees against data, the algorithm is then run against new data in a test set. Before algorithm training, a test set is randomly extracted from the original set.