Cybercrime: Identification and Prediction Using Machine Learning Techniques

Algorithm 1

K-Means algorithm.

	Step 1: Input X = {x1, x2, x3, …,xn} the set of data points
	Input: V =  the set of centers
	Step 2: Select “c” cluster centers randomly
	Step 3: The distance between each data point and cluster centers is calculated.
	Step 4: The data point to the cluster center whose distance from the cluster center is minimum of all the cluster centers is assigned.
	Step 5: The new cluster center is recalculated using:
	Where, “ci” represents the number of data points in ith cluster.
	Step 6: The distance between each data point and new obtained cluster centers is recalculated.
	Step 7: If no data point was reassigned then stop, otherwise repeat from step 3).