What is a kNN model?
Our method constructs a kNN model for the data, which replaces the data to serve as the basis of classification. The value of k is automatically determined, is varied for different data, and is optimal in terms of classification accuracy.
Is there a novel KNN type method for classification?
In this paper, we propose a novel kNN type method for classification that is aimed at overcoming these shortcomings. Our method constructs a kNN model for the data, which replaces the data to serve as the basis of classification.
What does KNN stand for?
The classification accuracy is calculated using K-nearest neighbours (KNN)  and classification and regression tree (CART) . The proposed method’s performance is compared to four existing state-of-the-art evolutionary-based approaches, namely GA , ACO , SLN , and PSO .
What are the disadvantages of kNN?
The major drawbacks with respect to kNN are (1) its low efficiency – being a lazy learning method prohibits it in many applications such as dynamic web mining for a large repository, and (2) its dependency on the selection of a “good value” for k .