A Comparative Study for Selecting the Best Unsupervised Learning Algorithm in e-Learning System
Clustering is one of the most important techniques of data mining. Clustering technique in data mining is an unsupervised machine learning algorithm that finds the groups of object such that objects in one group will be similar to one another and are dissimilar to the objects belonging to other clusters. Clustering is called unsupervised machine learning algorithm as groups are not predefined but defined by the data. So the most similar data are grouped into the clusters. In this paper, the authors compare five clustering algorithm namely Farthest first, Make Density Based Cluster, Simple K-means, EM, Hierarchical clustering algorithm for recommending the course to the student based on student course selection & present the result.