This paper describes an experiment where classifiers are used to identify potential diagnoses on examining textual content of medical records. Three classifiers are applied separately (k-nearest neighborhood, multilayer perceptron and support vector machines) and also combined in two different approaches (parallel and cascading); results show that even accuracy point to a best alternative, ROC ...

To better support forest sustainable management, this paper explores the technical framework for forest health assessment, and then focuses on how to better execute the evaluation part of this technical framework. Modular neural networks (MNN) have been shown to be more efficient for classification problems than the conventional monolithic artificial neural network. Therefore, this was used in ...

Given a set D of trajectories, a query object q, and a query time extent C, amutual (i.e., symmetric) nearest neighbor (MNN) query over trajectories finds from D, the set of trajectories that are among the k1 nearest neighbors (NNs) of q within C, and meanwhile, have q as one of their k2 NNs. This type of queries is useful inmany applications such as decisionmaking, data mining, and pattern rec...

Little is known about spatial inequalities and potential access to the food environment in rural areas. In this study, we assessed the food environment in a 6-county rural region of Texas (11,567 km2) through ground-truthed methods that included direct observation and on-site Global Positioning System technology to examine the relationship between neighborhood inequalities (e.g., socioeconomic ...

We present a data mining approach for reducing the search space of local search algorithms in large-scale set partitioning problems (SPPs). We construct a k-nearest neighbor graph by extracting variable associations from the instance to be solved, in order to identify promising pairs of flipping variables in the large neighborhood search. We incorporate the search space reduction technique into...

An evidence theoretic classification method is proposed in this paper. In order to classify a pattern we consider its neighbours, which are taken as parts of a single source of evidence to support the class membership of the pattern. A single mass function or basic belief assignment is then derived, and the belief function and the pignistic (“betting rates”) probability function can be calculat...

The inorganic layered crystal (ILC) MoS2 in low dimensions is considered as one of the most promising and efficient semiconductors. To enable the magnetism and keep intrinsic crystal structures, we carried out a first-principles study of the magnetic and semiconductive monolayer MoS2 adsorbed with the Mnn (n = 1-4) clusters, and bilayer MoS2 intercalated with the same clusters. Geometric optimi...