Author(s): RANKING INTERESTING RULES FOR RECOGNIZING BEST TEACHER USING MULTIDIMENSIONAL DATACUBE
Data Mining provides many technologies to detect the hidden patterns and predict an interestingness rules. Decision making and cluster is an important concept to group the related information and makes the better decision accordingly. Quality of education depends largely on teacher’s ability. This paper focuses the key problem in the teacher’s performance. The proposed method evaluates the Interesting Rules levels for recruiting best teacher. This method allows the user for to finding the rules classification to determine whether teacher can be recruited or not. The proposed idea is tested by extracted data from institution and results proven that it provides better accuracy.