Provisional Exceptional Property Pair Extraction Using Generic Approach

A noisy data elimination, attribute and property discovery is a major consideration in the proposed method. From the overall given population the system predicts the sub population effectively. The subpopulation and exceptional property pair which is known as outliers. With the aim of effective outlier detection, the proposed PEP algorithm applies a provisional model which identifies the exceptional property par with the best fit method implementation. There are several outlier detection methods have been introduced with certain domains and applications, but the techniques were more generic and suffer from confidentiality problem. The proposed concept effectively implements Genetic modal based approach which is named as GENEX algorithm and PEP algorithm for the detection of sub population scores for both numerical and categorical datasets. Additionally the system performs the best fit method in order to find best class based on the score and label. The proposed algorithm can reduce the computation cost and lack of accuracy problem by applying best data mining and suitable pruning techniques. The experiments and the results provides the mild and extreme outlier ranges with best fit values.