Due to the exponential growth of documents on the Internet and the emergent need to organize them, the automated categorization of documents into predefined labels has received an ever-increased attention in the recent years. A wide range of supervised learning algorithms has been introduced to deal with text classification. Among all these classifiers, K-Nearest Neighbors (KNN) is a widely use...

Currently, there has been an increasing development in the area of location-based service. An important type of query in this area is k nearest neighbor (kNN) query, which retrieves the top k nearest neighbors based on the user's position. Although a wide spectrum of work has been conducted on this query type, most of these studies focus on the ideal Euclidean plane without obstacles considered...

ML-kNN is a well-known algorithm for multi-label classification. Although effective in some cases, ML-kNN has some defect due to the fact that it is a binary relevance classifier which only considers one label every time. In this paper, we present a new method for multi-label classification, which is based on lazy learning approaches to classify an unseen instance on the basis of its k nearest ...

In this paper, we introduce Sequential Classifiers Combination (SCC) into text categorization to improve both the classification effectiveness and classification efficiency of the combined individual classifiers. We apply two classifiers sequentially for experimental study, where the first classifier (called filtering classifier) is used to generate candidate categories for the test document an...

Classification of spatial data streams is crucial, since the training dataset changes often. Building a new classifier each time can be very costly with most techniques. In this situation, k-nearest neighbor (KNN) classification is a very good choice, since no residual classifier needs to be built ahead of time. KNN is extremely simple to implement and lends itself to a wide variety of variatio...

A flood is an overflow of water and becomes the common natural disaster. Prediction of a flood is one of the challenges for disaster management around the world especially in developing countries. Thus, more accurate flood prediction models have been investigated according to the geographical locations. In this paper, we have studied and compared some useful machine learning models such as KNN,...