Efficient Feature Extraction Based on Regularized Uncorrelated Chernoff Discriminant Analysis

In this paper, two regularized uncorrelated Chernoff discriminant analysis (RUCDA) techniques are introduced. As a heteroscedastic extension of the class-wise weighted Fisher criterion, the class-wise weighted Chernoff criterion employed in RUCDA better approximates the Chernoff upper bound of the Bayes classification error in the transformed space, which enable the resulting RUCDA to extract uncorrelated discriminatory information from both mean and covariance differences. Experiments performed on UCI benchmark and protein secondary structure datasets demonstrate good performance of the proposed technique

[1]  Ponnuthurai Nagaratnam Suganthan,et al.  Benchmark Functions for the CEC'2013 Special Session and Competition on Large-Scale Global Optimization , 2008 .

[2]  Ponnuthurai Nagaratnam Suganthan,et al.  Unsupervised similarity-based feature selection using heuristic Hopfield neural networks , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

[3]  A. Kai Qin,et al.  Self-adaptive Differential Evolution Algorithm for Constrained Real-Parameter Optimization , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[4]  Jing J. Liang,et al.  Comprehensive learning particle swarm optimizer for global optimization of multimodal functions , 2006, IEEE Transactions on Evolutionary Computation.

[5]  P. Suganthan,et al.  Identification of catalytic residues from protein structure using support vector machine with sequence and structural features. , 2008, Biochemical and biophysical research communications.

[6]  Eam Khwang Teoh,et al.  On Attributed Relational Graph Matching Using Hopfield Network , 1994, European Conference on Artificial Intelligence.

[7]  K. G. Khoo,et al.  Objective function decomposition within genetic algorithm , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[8]  Ponnuthurai N. Suganthan,et al.  SMotif: a server for structural motifs in proteins , 2007, Bioinform..

[9]  A. Kai Qin,et al.  A novel kernel prototype-based learning algorithm , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[10]  Koh Giok. Khoo Attributed relational graph matching using genetic algorithm , 2002 .

[11]  Xin Yao,et al.  Linear dimensionality reduction using relevance weighted LDA , 2005, Pattern Recognit..

[12]  Hong Yan,et al.  Recognition of handprinted Chinese characters by constrained graph matching , 1998, Image Vis. Comput..

[13]  A. Kai Qin,et al.  Self-adaptive differential evolution algorithm for numerical optimization , 2005, 2005 IEEE Congress on Evolutionary Computation.

[14]  Mehmet Fatih Tasgetiren,et al.  A genetic algorithm for the generalized traveling salesman problem , 2007, 2007 IEEE Congress on Evolutionary Computation.

[15]  Mehmet Fatih Tasgetiren,et al.  A Discrete Differential Evolution Algorithm for the Total Earliness and Tardiness Penalties with a Common Due Date on a Single-Machine , 2007, 2007 IEEE Symposium on Computational Intelligence in Scheduling.

[16]  Ponnuthurai N. Suganthan,et al.  A novel concurrent particle swarm optimization , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[17]  Dinesh P. Mital,et al.  Programming Hopfield network for object recognition , 1993, Proceedings of IEEE Systems Man and Cybernetics Conference - SMC.

[18]  Kalyanmoy Deb,et al.  Multi-Class Protein Fold Recognition Using Multi-Objective Evolutionary Algorithms , 2004 .

[19]  Xin Yao,et al.  Feature Selection for Microarray Data Using Least Squares SVM and Particle Swarm Optimization , 2005, 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

[20]  Ponnuthurai N. Suganthan,et al.  On the performance of the HONG network for pattern classification , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

[21]  Ponnuthurai N. Suganthan,et al.  Combining classifiers based on confidence values , 1999, Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318).

[22]  P. Suganthan Attributed relational graph matching by neural-gas networks , 2000, Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501).

[23]  Ponnuthurai N. Suganthan Structure Adaptive Multilayer SOM with Partial Supervision for Numeral Recognition , 1997, ICONIP.

[24]  A. Kai Qin,et al.  Enhanced Direct Linear Discriminant Analysis for Feature Extraction on High Dimensional Data , 2005, AAAI.

[25]  Chris H. Q. Ding,et al.  Multi-class protein fold recognition using support vector machines and neural networks , 2001, Bioinform..

[26]  S. Baskar,et al.  Particle swarm optimization for the design of low-dispersion fiber Bragg gratings , 2005, IEEE Photonics Technology Letters.

[27]  A. Kai Qin,et al.  Enhanced neural gas network for prototype-based clustering , 2005, Pattern Recognit..

[28]  Dinesh P. Mital,et al.  Programming Hopfield network for relational homomorphism , 1994, Proceedings of TENCON'94 - 1994 IEEE Region 10's 9th Annual International Conference on: 'Frontiers of Computer Technology'.

[29]  Xin Yao,et al.  Gene selection algorithms for microarray data based on least squares support vector machine , 2006, BMC Bioinformatics.

[30]  Jing J. Liang,et al.  Performance Evaluation of Multiagent Genetic Algorithm , 2006, Natural Computing.

[31]  P. Suganthan,et al.  Shape Indexing Using Relational Vectors and Neural Networks , 2001 .

[32]  Tao Jiang,et al.  Efficient and robust feature extraction by maximum margin criterion , 2003, IEEE Transactions on Neural Networks.

[33]  Robert P. W. Duin,et al.  Linear dimensionality reduction via a heteroscedastic extension of LDA: the Chernoff criterion , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[34]  D. Atukorale,et al.  Comparing performances of supervised classifiers , 2000 .

[35]  Xiang Cao,et al.  Video Sequence Boundary Detection Using Neural Gas Networks , 2001, ICANN.

[36]  Jing J. Liang,et al.  Dynamic multi-swarm particle swarm optimizer , 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..

[37]  A. Kai Qin,et al.  Evolutionary extreme learning machine , 2005, Pattern Recognit..

[38]  Jing J. Liang,et al.  A new generalized LVQ algorithm via harmonic to minimum distance measure transition , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[39]  Ponnuthurai N. Suganthan,et al.  Concurrent PSO and FDR-PSO based reconfigurable phase-differentiated antenna array design , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[40]  Xiang Cao,et al.  Neural Network Based Temporal Video Segmentation , 2002, Int. J. Neural Syst..

[41]  Jing J. Liang,et al.  Dynamic Multi-Swarm Particle Swarm Optimizer with a Novel Constraint-Handling Mechanism , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[42]  Ponnuthurai Nagaratnam Suganthan,et al.  Design of triangular FBG filter for sensor applications using covariance matrix adapted evolution algorithm , 2006 .

[43]  Eam Khwang Teoh,et al.  Learning parameters for object recognition by the self-organizing Hopfield network , 1996 .

[44]  Ponnuthurai Nagaratnam Suganthan,et al.  Fiber Bragg grating sensor array interrogation using differential evolution , 2008 .

[45]  Dinesh P. Mital,et al.  Fuzzy connectives based optimal mapping of homomorphic ARG matching onto self-organising Hopfield network , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[46]  A. Kai Qin,et al.  Kernel neural gas algorithms with application to cluster analysis , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[47]  Mehmet Fatih Tasgetiren,et al.  A Multi-Populated Differential Evolution Algorithm for Solving Constrained Optimization Problem , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[48]  Ponnuthurai Nagaratnam Suganthan,et al.  Improving the performance of a FBG sensor network using a novel dynamic multi-swarm particle swarm optimizer , 2005, SPIE Optics East.

[49]  P.N. Suganthan,et al.  Growing generalized learning vector quantization with local neighborhood adaptation rule , 2004, 2004 2nd International IEEE Conference on 'Intelligent Systems'. Proceedings (IEEE Cat. No.04EX791).

[50]  Ponnuthurai Nagaratnam Suganthan Structure adaptive multilayer overlapped SOMs with supervision for handprinted digit classification , 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

[51]  P. N. Suganthan,et al.  Hierarchical overlapped growing neural gas networks with applications to video shot detection and motion characterization , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

[52]  Ponnuthurai N. Suganthan,et al.  An Accumulation Algorithm for Video Shot Boundary Detection , 2004, Multimedia Tools and Applications.

[53]  Jing J. Liang,et al.  Problem Deflnitions and Evaluation Criteria for the CEC 2006 Special Session on Constrained Real-Parameter Optimization , 2006 .

[54]  P. N. Suganthan,et al.  Robust growing neural gas algorithm with application in cluster analysis , 2004, Neural Networks.

[55]  Carlos E. Thomaz,et al.  A new covariance estimate for Bayesian classifiers in biometric recognition , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[56]  Mehmet Fatih Tasgetiren,et al.  A Discrete Differential Evolution Algorithm for the No-Wait Flowshop Scheduling Problem with Total Flowtime Criterion , 2007, 2007 IEEE Symposium on Computational Intelligence in Scheduling.

[57]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[58]  Xin Yao,et al.  Nonlinear Feature Extraction Using Evolutionary Algorithm , 2004, ICONIP.

[59]  K. G. Khoo,et al.  Multiple relational graphs mapping using genetic algorithms , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[60]  Mehmet Fatih Tasgetiren,et al.  Multi-objective optimization based on self-adaptive differential evolution algorithm , 2007, 2007 IEEE Congress on Evolutionary Computation.

[61]  Ponnuthurai N. Suganthan,et al.  Structural pattern recognition using genetic algorithms , 2002, Pattern Recognit..

[62]  Xudong Jiang,et al.  Fingerprint image quality analysis , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[63]  Ponnuthurai N. Suganthan Pattern classification using multiple hierarchical overlapped self-organising maps , 2001, Pattern Recognit..

[64]  Eam Khwang Teoh,et al.  Hopfield network with constraint parameter adaptation for overlapped shape recognition , 1999, IEEE Trans. Neural Networks.

[65]  Jing J. Liang,et al.  Comprehensive learning particle swarm optimizer for solving multiobjective optimization problems , 2006, Int. J. Intell. Syst..

[66]  Robert P. W. Duin,et al.  Multiclass Linear Dimension Reduction by Weighted Pairwise Fisher Criteria , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[67]  Hong Yan,et al.  Optimal encoding of graph homomorphism energy using fuzzy information aggregation operators , 1998, Pattern Recognit..

[68]  Jing J. Liang,et al.  Particle swarm optimization algorithms with novel learning strategies , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[69]  Ponnuthurai N. Suganthan,et al.  Improved MOCLPSO algorithm for environmental/economic dispatch , 2007, 2007 IEEE Congress on Evolutionary Computation.

[70]  Ponnuthurai N. Suganthan,et al.  MegaMotifBase: a database of structural motifs in protein families and superfamilies , 2008, Nucleic Acids Res..

[71]  Ponnuthurai N. Suganthan,et al.  Evaluation of genetic operators and solution representations for shape recognition by genetic algorithms , 2002, Pattern Recognit. Lett..

[72]  Ponnuthurai N. Suganthan,et al.  LisBON: A framework for parallelisation and hybridisation of optimisation algorithms , 2007, 2007 IEEE Congress on Evolutionary Computation.

[73]  P. N. Suganthan,et al.  Multiobjective Differential Evolution with External Archive and Harmonic Distance-Based Diversity Measure , 2007 .

[74]  Jing J. Liang,et al.  Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization , 2005 .

[75]  Nikhil R. Pal,et al.  Pattern Classification Using Multiple SOMs , 1998, ICONIP.

[76]  Xiang Cao,et al.  Video shot motion characterization based on hierarchical overlapped growing neural gas networks , 2003, Multimedia Systems.

[77]  Ponnuthurai N. Suganthan,et al.  Hierarchical overlapped neural gas network with application to pattern classification , 2000, Neurocomputing.

[78]  Jing J. Liang,et al.  Adaptive Comprehensive Learning Particle Swarm Optimizer with History Learning , 2006, SEAL.

[79]  Jing-Yu Yang,et al.  Face recognition based on the uncorrelated discriminant transformation , 2001, Pattern Recognit..

[80]  Michel Verleysen,et al.  Advances in Self Organising Maps , 2006, ArXiv.

[81]  Ponnuthurai N. Suganthan,et al.  Feature Analysis and Classification of Protein Secondary Structure Data , 2003, ICANN.

[82]  S. Baskar,et al.  Design of optimal length low-dispersion FBG filter using covariance matrix adapted evolution , 2005, IEEE Photonics Technology Letters.

[83]  Ponnuthurai N. Suganthan,et al.  Structural pattern recognition using genetic algorithms with specialized operators , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[84]  Ponnuthurai N. Suganthan,et al.  A multi-layered solution for supporting isp traffic demand using genetic algorithm , 2007, 2007 IEEE Congress on Evolutionary Computation.

[85]  Dinesh P. Mital,et al.  Learning critical temperature for homomorphic ARG matching by self-organising Hopfield network , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[86]  Kalyanmoy Deb,et al.  A novel fuzzy and multiobjective evolutionary algorithm based gene assignment for clustering short time series expression data , 2007, 2007 IEEE Congress on Evolutionary Computation.

[87]  Xin Yao,et al.  Generalized LDA using relevance weighting and evolution strategy , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[88]  A. Kai Qin,et al.  Initialization insensitive LVQ algorithm based on cost-function adaptation , 2005, Pattern Recognit..

[89]  Ponnuthurai Nagaratnam Suganthan,et al.  Genetic‐algorithm‐based design of a reconfigurable antenna array with discrete phase shifters , 2005 .

[90]  Jieping Ye,et al.  Characterization of a Family of Algorithms for Generalized Discriminant Analysis on Undersampled Problems , 2005, J. Mach. Learn. Res..

[91]  Ponnuthurai N. Suganthan Shape indexing using self-organizing maps , 2002, IEEE Trans. Neural Networks.

[92]  Ponnuthurai N. Suganthan,et al.  Combining multiple HONG networks for recognizing unconstrained handwritten numerals , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

[93]  P.N. Suganthan,et al.  Generalized null space uncorrelated Fisher discriminant analysis for linear dimensionality reduction , 2006, Pattern Recognit..

[94]  Ponnuthurai N. Suganthan,et al.  Feature Selection Approach for Quantitative Prediction of Transcriptional Activities , 2006, 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology.

[95]  Jian Yang,et al.  What's wrong with Fisher criterion? , 2002, Pattern Recognit..

[96]  Ponnuthurai Nagaratnam Suganthan,et al.  Multiple HONG network fusion by fuzzy integral , 1999, ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378).

[97]  Jing J. Liang,et al.  Dynamic multi-swarm particle swarm optimizer with local search , 2005, 2005 IEEE Congress on Evolutionary Computation.

[98]  Xin Yao,et al.  An analysis of diversity measures , 2006, Machine Learning.

[99]  Jing J. Liang,et al.  Evaluation of Comprehensive Learning Particle Swarm Optimizer , 2004, ICONIP.

[100]  Ponnuthurai Nagaratnam Suganthan,et al.  Improving the performance of the HONG network with boosting , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

[102]  Ponnuthurai Nagaratnam Suganthan,et al.  An adaptive cumulation algorithm for video shot detection , 2001, Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing. ISIMP 2001 (IEEE Cat. No.01EX489).

[103]  John W. Sammon,et al.  An Optimal Set of Discriminant Vectors , 1975, IEEE Transactions on Computers.

[104]  A. Kai Qin,et al.  Personal Identification System based on Multiple Palmprint Features , 2006, 2006 9th International Conference on Control, Automation, Robotics and Vision.

[105]  Hong Yan,et al.  Handwritten Chinese character recognition by ARG matching using self-organising Hopfield neural network , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

[106]  Eam Khwang Teoh,et al.  Optimal mapping of graph homomorphism onto self organising Hopfield network , 1997, Image Vis. Comput..

[107]  Ganesan Pugalenthi,et al.  Predicting protein structural class by SVM with class-wise optimized features and decision probabilities. , 2008, Journal of theoretical biology.

[108]  Jing J. Liang,et al.  Novel composition test functions for numerical global optimization , 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..

[109]  Ponnuthurai N. Suganthan,et al.  A machine learning approach for the identification of odorant binding proteins from sequence-derived properties , 2007, BMC Bioinformatics.

[110]  Keinosuke Fukunaga,et al.  Introduction to Statistical Pattern Recognition , 1972 .

[111]  P.N. Suganthan,et al.  A Robust Neural Gas algorithm for clustering analysis , 2004, International Conference on Intelligent Sensing and Information Processing, 2004. Proceedings of.