Nearest neighbor searching is an important geometric subproblem in vector quantization. Existing studies have shown that the difficulty of solving this problem efficiently grows rapidly with dimension. Indeed, existing approaches on unstructured codebooks in dimension 16 are little better than brute-force search. We show that if one is willing to relax the requirement of finding the true neares...

Keywords: Double fuzzy topology Double neighborhood systems Double fuzzy preproximity Double fuzzy closure space a b s t r a c t In this paper, we introduce the notions of double neighborhood systems and double fuzzy preproximity in double fuzzy topological spaces. We used double neighborhoods to study the initial structure of double fuzzy topological spaces, and the joins between them and the ...

A. Introduction Recommendation systems are an active topic in research and industry. The technique of collaborative filtering is especially successful in generating personalized recommendations. More than a decade of research has resulted in numerous algorithms, out of which, we have chosen K-Nearest Neighborhood (K-NN) model to predict the ratings for the songs. This model is an item-based alg...

K-nearest neighbor (KNN) is an effective nonparametric classifier that determines the neighbors of a point based only on distance proximity. The classification performance KNN disadvantaged by presence outliers in small sample size datasets and its deteriorates with class imbalance. We propose local Bonferroni Mean Fuzzy K-Nearest Centroid Neighbor (BM-FKNCN) assigns label query dependent neare...

The weighted sampling methods based on k-nearest neighbors have been demonstrated to be effective in solving the class imbalance problem. However, they usually ignore positional relationship between a sample and heterogeneous samples its neighborhood when calculating weight. This paper proposes novel neighborhood-weighted method named NWBBagging improve Bagging algorithm's performance imbalance...

Nearest Neighbor Search plays a vital role in building road-maps in Motion Planning. These are implemented in any Road-map building method such as PRM, OBPRM, Gauss PRM, etc. Motion Planning is the science of designing a successfully implementable plan in any Configuration Space (often called C-space) in order to move the Robot from a given Start Configuration to a Goal Configuration by avoidin...

OBJECTIVE To determine the extent to which neighborhood needs (socioeconomic deprivation and vehicle availability) are associated with two criteria of food environment access: 1) distance to the nearest food store and fast food restaurant and 2) coverage (number) of food stores and fast food restaurants within a specified network distance of neighborhood areas of colonias, using ground-truthed ...

Topological methods have been successfully used to identify features in scalar fields and to measure their importance. In this paper, we define a notion of topological saliency that captures the relative importance of a topological feature with respect to other features in its local neighborhood. Features are identified by extreme points of an input scalar field, and their importance measured b...