Educational Data Clustering in a Weighted Feature Space Using Kernel K-Means and Transfer Learning Algorithms
Educational Data Clustering in a Weighted Feature Space Using Kernel K-Means and Transfer Learning Algorithms
Educational data clustering on the students’ data collected with a program can find several groups of the students sharing the similar characteristics in their behaviors and study performance. For some programs, it is not trivial for us to prepare enough data for the clustering task. Data shortage might then influence the effectiveness of the clustering process and thus, true clusters can not be discovered appropriately.