K-Means Clustering Algorithm
K-means is a classical clustering algorithm based on unsupervised learning. The main idea is to assign each data point to a predefined set of clusters (k). The initial location assignments of the cluster should be done in a cunning way as the proceeding results depends on these initializations. Details of this promising algorithms are provided in the next section.
Objective:
The objective of this algorithm is to minimize a squared error function which is given below:
