International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 106 - Number 3 |
Year of Publication: 2014 |
Authors: Roshani Ade, P. R. Deshmukh |
10.5120/18504-9580 |
Roshani Ade, P. R. Deshmukh . Instance-based vs Batch-based Incremental Learning Approach for Students Classification. International Journal of Computer Applications. 106, 3 ( November 2014), 37-41. DOI=10.5120/18504-9580
It is difficult to find the hidden information in the educational database system, because of the rapid increase of the student's data. The hidden information from the educational databases can be used for the various predictions like students' performance, offering different career choices to students, prediction of student's enrollment into various courses and many more. This data can be learned incrementally by using instance based or batch based approach. The instance based method is just like an online learning, the system will handle each instance incrementally, the algorithm itself is an updatable, and the knowledge will be updated by every instance in time. In the batch based approach, instances are coming in the batches and will be operated in a bulk, so the processing time requires for it is less as compared to instance based approach and learning new concept is possible when the data is available in a batches. The paper proposes three approaches of incremental learning and compares for handling students data and compares the results of the same.