CFSBFDroid: Android Malware Detection Using CFS + Best First Search-Based Feature Selection

Algorithm 1

Pseudocode of random forest (RF).

	Input (RF) : A training set (RF)
(1)	It randomly selects the “k” attributes from the dataset.
(2)	It uses the Gini index for the best split, selects the root node, and forms multiple decision trees.
(3)	The forecast is made based on the outcome of these decision trees.
(4)	Finally, calculate the number of votes for each class label. The highest voted class becomes the predicted class.
	Output: Classified Instances