An assay of teachers' attainmentusing decision tree based classification techniques

Data mining is one of the potential research fields regarding interdisciplinary aspects. Educational data mining is one the developing discipline in the present junction. Classification techniques in the data mining plays an important role in the area of educational data mining. The main goal regarding this work is to predict the teachers' attainment by using the relevant features. The proposed methodology consists of the phases like preprocessing, attribute selection, classification based on decision tree and performance evaluation. In the data preprocessing phase, the missing values have been removed. The attributes are remodel into a categorized format using the categorization process. Gain ratio, chi square and information gain feature selection methods are tested on preprocessed data. The suitable attributes selected are predicted using classification techniques. In this paper, one of the classification techniques are described and based on ID3, C4.5 and C5.0 is used to predict the teachers' attainment in educational data mining.