We describe a new method for performing a nonlinear form of Principal Component Analysis. By the use of integral operator kernel functions, we can e ciently compute principal comp...
When using a Genetic Algorithm (GA) to optimize the feature space of pattern classification problems, the performance improvement is not only determined by the data set used, but a...
Zhijian Huang, Min Pei, Erik D. Goodman, Yong Huan...
In this paper we address two aspects related to the exploitation of Support Vector Machines (SVM) for classification in real application domains, such as the detection of objects ...
In this paper, we introduce the concepts of "cooperative buildings" and "roomware" and place them in the context of the integrated design of real, physical, res...
In this paper we compared the performance of the Automatic Data Reduction System (ADRS) and principal component analysis (PCA) as a preprocessor to artificial neural networks (ANN...
Nicholas Navaroli, David Turner, Arturo I. Concepc...