Dissimilarity representations allow for building good classifiers

Authors:
Elzbieta Pekalska;Robert P. W. Duin
Affiliations:
Pattern Recognition Group, Laboratory of Applied Physics, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft, The Netherlands;Pattern Recognition Group, Laboratory of Applied Physics, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft, The Netherlands
Venue:
Pattern Recognition Letters
Year:
2002

Citing 6
Cited 46

Introduction to statistical pattern recognition (2nd ed.)

Introduction to statistical pattern recognition (2nd ed.)
Instance-Based Learning Algorithms

Machine Learning
Representation and recognition in vision

Representation and recognition in vision
Relational discriminant analysis

Pattern Recognition Letters - Special issue on pattern recognition in practice VI
Pattern Recognition and Neural Networks

Pattern Recognition and Neural Networks
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)

Dissimilarity-based classification of spectra: computational issues

Real-Time Imaging - Special issue on spectral imaging
One-class classifier for HFGWR ship detection using similarity-dissimilarity representation

IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Multi-resolution subspace for financial trading

Pattern Recognition Letters
Similarity learning via dissimilarity space in CBIR

MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Experimental study on prototype optimisation algorithms for prototype-based classification in vector spaces

Pattern Recognition
Moderate diversity for better cluster ensembles

Information Fusion
Prototype selection for dissimilarity-based classifiers

Pattern Recognition
Direct classification of high-dimensional data in low-dimensional projected feature spaces-Comparison of several classification methodologies

Journal of Biomedical Informatics
Off-line signature verification based on forensic questioned document examination approach

Proceedings of the 2007 ACM symposium on Applied computing
On learning with dissimilarity functions

Proceedings of the 24th international conference on Machine learning
On using prototype reduction schemes to optimize dissimilarity-based classification

Pattern Recognition
A nearest-neighbor approach to relevance feedback in content based image retrieval

Proceedings of the 6th ACM international conference on Image and video retrieval
Author identification using writer-dependent and writer-independent strategies

Proceedings of the 2008 ACM symposium on Applied computing
Evolution of Multi-class Single Layer Perceptron

ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
On Combining Dissimilarity-Based Classifiers to Solve the Small Sample Size Problem for Appearance-Based Face Recognition

CAI '07 Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Minimizing the Imbalance Problem in Chromatographic Profile Classification with One-Class Classifiers

ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
A generalization of dissimilarity representations using feature lines and feature planes

Pattern Recognition Letters
An Inexact Graph Comparison Approach in Joint Eigenspace

SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Theory and algorithm for learning with dissimilarity functions

Neural Computation
Dissimilarity-based classification in the absence of local ground truth: Application to the diagnostic interpretation of chest radiographs

Pattern Recognition
Fast communication: Local aggregation function learning based on support vector machines

Signal Processing
Chromatographic Pattern Recognition Using Optimized One-Class Classifiers

IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Reducing forgeries in writer-independent off-line signature verification through ensemble of classifiers

Pattern Recognition
Content based image retrieval using unclean positive examples

IEEE Transactions on Image Processing
A naive relevance feedback model for content-based image retrieval using multiple similarity measures

Pattern Recognition
Image retrieval using noisy query

ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Combination of generative models and SVM based classifier for speech emotion recognition

IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
An adaptive unsupervised approach toward pixel clustering and color image segmentation

Pattern Recognition
Similarity-based classification of sequences using hidden Markov models

Pattern Recognition
Similarity-based clustering of sequences using hidden Markov models

MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
Generalizing dissimilarity representations using feature lines

CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Dissimilarity-based multiple instance learning

SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Image dissimilarity-based quantification of lung disease from CT

MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
Similarity-margin based feature selection for symbolic interval data

Pattern Recognition Letters
Automatic segmentation of digitalized historical manuscripts

Multimedia Tools and Applications
Multi-task regularization of generative similarity models

SIMBAD'11 Proceedings of the First international conference on Similarity-based pattern recognition
Taxonomy of classifiers based on dissimilarity features

ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
On optimizing dissimilarity-based classification using prototype reduction schemes

ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
On using a dissimilarity representation method to solve the small sample size problem for face recognition

ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Cascade of fusion for adaptive classifier combination using context-awareness

AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Optimizing dissimilarity-based classifiers using a newly modified hausdorff distance

PKAW'06 Proceedings of the 9th Pacific Rim Knowledge Acquisition international conference on Advances in Knowledge Acquisition and Management
The dissimilarity representation for structural pattern recognition

CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Class proximity measures - Dissimilarity-based classification and display of high-dimensional data

Journal of Biomedical Informatics
One-sided prototype selection on class imbalanced dissimilarity matrices

SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
On the dissimilarity representation and prototype selection for signature-based bio-cryptographic systems

SIMBAD'13 Proceedings of the Second international conference on Similarity-Based Pattern Recognition
A bio-cryptographic system based on offline signature images

Information Sciences: an International Journal

Quantified Score

Hi-index	0.10

Visualization

Abstract

In this paper, a classification task on dissimilarity representations is considered. A traditional way to discriminate between objects represented by dissimilarities is the nearest neighbor method. It suffers, however, from a number of limitations, i.e., high computational complexity, a potential loss of accuracy when a small set of prototypes is used and sensitivity to noise. To overcome these shortcomings, we propose to use a normal density-based classifier constructed on the same representation. We show that such a classifier, based on a weighted combination of dissimilarities, can significantly improve the nearest neighbor rule with respect to the recognition accuracy and computational effort.