UNIQUE DATA MINING APPROACH TO PREDICT PLACEMENT CHANCE

Data mining is an effective methodology, which can be used to analyze large amount of data to produce hidden patterns and relationships. The main idea proposed is analyzing the law student's historical data and predicting the appropriate, qualitative specialization chances. A student enters his/her rank, gender, sector and reservation category, and this model predicts specialization that suits for entered student as example with criminal law as E(excellent) and civil law as P(poor) based on the entered information. Different algorithm s were applied for same set of data and comparison will be made in terms of accuracy, precision and truth positive rate. This paper will work for law students selecting a best specialization for them which ensures best carrier based on data entered. A mode l is proposed where in a latest algorithm, one from each different category of models such as clustering, classification and association models are selected and applied on the same dataset. Hence the name CCA model. Rock algorithm from Clustering, Naïve ba ye's from classification and frequent pattern algorithm from Association models are selected. These algorithms are applied, to predict accurately one among the various courses offered which predict better placement chances. Student will enter Rank, Gender, Category and Sector and the model will give answer in terms of Excellent [E], Good [G], Average [A] and Poor [P] for the data entered. Algorithms are compared in terms of precision, accuracy and truth positive rate. From the results obtained it is found t hat the Clustering model predicts better in comparison with other two models. This work will help the students in selecting a best course suitable for them which ensure better placement based on the data entered.