A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Unsupervised Learning of Finite Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient greedy learning of Gaussian mixture models
Neural Computation
Improving similarity measures of histograms using smoothing projections
Pattern Recognition Letters
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Simple Gabor feature space for invariant object recognition
Pattern Recognition Letters
Feature-Based Affine-Invariant Localization of Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Reliability estimation of a statistical classifier
Pattern Recognition Letters
Designing multi-rover emergent specialization
Proceedings of the 10th annual conference on Genetic and evolutionary computation
On EM Estimation for Mixture of Multivariate t-Distributions
Neural Processing Letters
Neuro-evolution approaches to collective behavior
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Collective specialization for evolutionary design of a multi-robot system
SAB'06 Proceedings of the 2nd international conference on Swarm robotics
Object class detection using local image features and point pattern matching constellation search
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Pattern recognition using boundary data of component distributions
Computers and Industrial Engineering
Novelty Detection with Multivariate Extreme Value Statistics
Journal of Signal Processing Systems
Person recognition using human head motion information
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Cluster-based adaptive metric classification
Neurocomputing
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Understanding the coverage and scalability of place-centric crowdsensing
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Review: A review of novelty detection
Signal Processing
Hi-index | 0.01 |
This study promotes the use of statistical methods in specific classification tasks since statistical methods have certain advantages which advocate their use in pattern recognition. One central problem in statistical methods is estimation of class conditional probability density functions based on examples in a training set. In this study maximum likelihood estimation methods for Gaussian mixture models are reviewed and discussed from a practical point of view. In addition, good practices for utilizing probability densities in feature classification and selection are discussed for Bayesian and, more importantly, for non-Bayesian tasks. As a result, the use of confidence information in the classification is proposed and a method for confidence estimation is presented. The propositions are tested experimentally.