The main two drawbacks of nearest neighbor based classifiers are: high CPU costs when the number of samples in the training set is high and performance extremely sensitive to outliers. Several attempts of overcoming such drawbacks have been proposed in the pattern recognition field aimed at selecting/gen-erating an adequate subset of prototypes from the training set. The problem addressed in th...

Nearest neighbor classification expects the class conditional probabilities to be locally constant. The assumption becomes invalid in high dimension due to the curse−of−dimensionality. Severe bias can be introduced under this condition when using nearest neighbor rule. We propose an adaptive nearest neighbor classification method ¡°indecisive classifier¡± to minimize bias and variance by avoidi...

Nearest-neighbor search dominates the asymptotic complexity of sampling-based motion planning algorithms and is often addressed with k-d tree data structures. While it is generally believed that the expected complexity of nearest-neighbor queries is O(log(N)) in the size of the tree, this paper reveals that when a classic k-d tree approach is used with sub-Riemannian metrics, the expected query...

In the panoply of pattern classification techniques, few enjoy the intuitive appeal and simplicity of the nearest neighbor rule: given a set of samples in some domain space whose value under some function is known, estimate the function anywhere in the domain by giving the value of the nearest sample (relative to some metric). More generally, one may use the modal value of the m nearest samples...

Higher Education, or tertiary education, is the final stage which optional in formal education. It usually organized form of a university, academy, seminary, high school, institute. Every institution needs qualified and professional educators because they have an important role process implementing Tri Dharma Education. Recruitment for teaching staff has several stages standardization assessmen...

Nowadays, people’s demand for indoor location information is more and more, which continuously promotes the development of positioning technology. In field positioning, fingerprint based algorithm still accounts a large proportion. However, operation this method in offline stage too cumbersome time-consuming, makes its disadvantages obvious, requires lot manpower time to sample mainta...

Distance-based approaches to outlier detection are popular in data mining, as they do not require to model the underlying probability distribution, which is particularly challenging for high-dimensional data. We present an empirical comparison of various approaches to distance-based outlier detection across a large number of datasets. We report the surprising observation that a simple, sampling...