Use of Classification Technique in Educational Data Mining

Use of Classification Technique in Educational Data Mining

연구 분야: Databases

학회: 2021 4th Biennial International Conference on Nascent Technologies in Engineering (ICNTE)

Data Mining is the process of identifying the hidden pattern from huge amount of data while Educational data mining is the technique used for automatically extracting the meaning from data that come from educational setting. Data mining algorithms are classification, clustering, association rule etc. Out of these algorithms, here the use of classification algorithm in Educational Data Mining for predicting the class (Distinction, First, Second, Pass, Fail, ATKT) obtained by the student in the university examination. In the current study, various classification algorithms results such as RandomForest, J48, SimpleCart, DecisionTable, NaiveBays, SMO, and SimpleLogistic are compared and finally the algorithm RandomForest is considered to explain the classification technique. Training set is used to train the algorithm for classification rule and test set is used to check whether classification rule correctly classified the test data. In this article, the results are also discussed whether the predicted class of test data is matched with the actual data.