We examine the learning-curve sampling method, an approach for applying machinelearning algorithms to large data sets. The approach is based on the observation that the computatio...
Geographical Information Systems (GIS) involve the manipulation of large spatial data sets, and the performance of these systems is often determined by how these data sets are orga...
Akhil Kumar, Waleed A. Muhanna, Raymond A. Patters...
This study looks at the relationships between different methods of classifier combination and different measures of diversity. We considered ten combination methods and ten measur...
ns, with large, abstract, multidimensional data sets that are visually represented in multiple ways. We illustrate how spreadsheet techniques provide a structured, intuitive, and p...
Ed Huai-hsin Chi, John Riedl, Phillip Barry, Josep...
an abstract model for information sharing and integration and use it to develop an architecture for building open, component-based, interoperable systems. A geographic information ...
When data sets are analyzed, statistical pattern recognition is often used to find the information hidden in the data. Another approach to information discovery is data mining. Dat...
In this paper we present a hierarchical approach for the deformable surface technique. This technique is a three dimensional extension of the snake segmentation method. We use it ...
: A new dynamic tree structured network - the Stochastic Competitive Evolutionary Neural Tree (SCENT) is introduced. The network is able to provide a hierarchical classification of...
The goal of discriminant analysis is to obtain rules that describe the separation between groups of observations. Moreover it allows to classify new observations into one of the k...
Background: Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very f...