Over the last decade, an immense amount of data has become available. From collections of photos, to genetic data, and to network traffic statistics, modern technologies and cheap storage have made it possible to accumulate huge datasets. But how can we effectively use all this data? The ever growing sizes of the datasets make it imperative to design new algorithms capable of sifting through th...

Given a set S of points in a metric space with distance function D, the nearest-neighbor searching problem is to build a data structure for S so that for an input query point q, the point s ∈ S that minimizes D(s, q) can be found quickly. We survey approaches to this problem, and its relation to concepts of metric space dimension. Several measures of dimension can be estimated using nearest-nei...

In this paper, we propose novel methods to find the best relevant feature subset using fuzzy rough set-based attribute subset selection with biologically inspired algorithm search such as ant colony and particle swarm optimization and the principles of an evolutionary process. We then propose a hybrid fuzzy rough with K-nearest neighbor (KNN)-based classifier (FRNN) to classify the patterns in ...

Collection of appropriate qualitative and quantitative data is necessary for proper management and planning. Used the suitable inventory methods is necessary and accuracy of sampling methods dependent the inventory net and number of sample point. Nearest neighbor sampling method is a one of distance methods and calculated by three equations (Byth and Riple, 1980; Cotam and Curtis, 1956 and Cota...

collection of appropriate qualitative and quantitative data is necessary for proper management and planning. used the suitable inventory methods is necessary and accuracy of sampling methods dependent the inventory net and number of sample point. nearest neighbor sampling method is a one of distance methods and calculated by three equations (byth and riple, 1980; cotam and curtis, 1956 and cota...

Various classical techniques such as linear regression, nearest neighbor have been used in developing predictive models in the past. But the methodologies developed using fuzzy time series includes a wide array of work that requires special attention. The time series analysis has been of great importance to engineering and economy problems. In this paper, we present a brief summary of the vario...