Integration of lazy learning associative classification with kNN algorithm

With the improvement of web sources and the progression of science and innovation, a huge amount of data has been generated and stored. A proper and accurate classification system is in need for those datasets, so that its information can be utilized in the betterment of the society. In this paper, a new method for classification system is presented by integrating lazy learning associative classification and kNN algorithm. The proposed lazy learning associative classifier generates a good quality nearest neighbor class association rules based on the test query and predicts the class label. The experimental results shows that the propsed lazy kNN associate classifer shows betters accuracy when compared with existing lazy learning associative classier.

I. Introduction

We are living in the digital age where everything is processed digitally and we are generating a numerous amount of data. To store all the generated data, handle the data and extract useful information is a challenging task.