Titlebook: Data Complexity in Pattern Recognition; Mitra Basu,Tin Kam Ho Book 2006 Springer-Verlag London 2006 algorithm.algorithms.classification.cl

Absenteeism

Data Complexity and Evolutionary Learningefits from the long experience and research in the area. We describe the XCS learning mechanisms by which a set of rules describing the class boundaries is evolved. We study XCS’s behavior and its relationship to data complexity. We find that the difficult cases for XCS are those with long boundarie

減少

aphasia

Data Complexity Issues in Grammatical Inferencege theory, syntactic and structural pattern recognition, computational linguistics, computational biology, and speech recognition. Specificities of the problems that are studied include those related to data complexity. We argue that there are three levels at which data complexity for grammatical in

天真

Simple Statistics for Complex Feature Spacestterns in high-dimensional feature spaces, with a view to gaining insight into the complexity of classification tasks. Pattern vectors from several data sets of printed and hand-printed digits are standardized to identity covariance matrix variables via principal component analysis, shifting to zero

膽汁

Polynomial Time Complexity Graph Distance Computation for Web Content Miningolynomial time problem. Calculating the maximum common subgraph is useful for creating a graph distance measure, since we observe that graphs become more similar (and thus have less distance) as their maximum common subgraphs become larger and vice versa. With a computationally practical method of d

Cardioversion

滲透

Complexity of Magnetic Resonance Spectrum Classificationmagnetic resonance spectra for two-class discrimination. Results suggest that for this typical problem with sparse samples in a high-dimensional space, even robust classifiers like random decision forests can benefit from sophisticated feature selection procedures, and the improvement can be explain

Mortal

Irrepressible

Human-Computer Interaction for Complex Pattern Recognition Problemse tasks to exploit the differences between human and machine capabilities. Human involvement offers advantages, both in the design of automated pattern classification systems, and at the operational level of some image retrieval and classification tasks. Recent development of interactive systems has