Machine Learning
BAS: a perceptual shape descriptor based on the beam angle statistics
Pattern Recognition Letters
How boosting the margin can also boost classifier complexity
ICML '06 Proceedings of the 23rd international conference on Machine learning
Fast Kernel Classifiers with Online and Active Learning
The Journal of Machine Learning Research
LIBLINEAR: A Library for Large Linear Classification
The Journal of Machine Learning Research
A New Variant of the Optimum-Path Forest Classifier
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Supervised pattern classification based on optimum-path forest
International Journal of Imaging Systems and Technology - Contemporary Challenges in Combinatorial Image Analysis
Introduction to Algorithms, Third Edition
Introduction to Algorithms, Third Edition
Synergistic arc-weight estimation for interactive image segmentation using graphs
Computer Vision and Image Understanding
Fast and accurate holistic face recognition using optimum-path forest
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Fast interactive segmentation of natural images using the image foresting transform
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Spoken emotion recognition through optimum-path forest classification using glottal features
Computer Speech and Language
Engineering Applications of Artificial Intelligence
Optimizing Optimum-Path Forest Classification for Huge Datasets
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Fast automatic microstructural segmentation of ferrous alloy samples using optimum-path forest
CompIMAGE'10 Proceedings of the Second international conference on Computational Modeling of Objects Represented in Images
Aquatic weed automatic classification using machine learning techniques
Computers and Electronics in Agriculture
An Optimum-Path Forest framework for intrusion detection in computer networks
Engineering Applications of Artificial Intelligence
ECG arrhythmia classification based on optimum-path forest
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A relevance feedback approach for the author name disambiguation problem
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
A data reduction and organization approach for efficient image annotation
Proceedings of the 28th Annual ACM Symposium on Applied Computing
A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest
Expert Systems with Applications: An International Journal
Pattern Recognition Letters
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Today data acquisition technologies come up with large datasets with millions of samples for statistical analysis. This creates a tremendous challenge for pattern recognition techniques, which need to be more efficient without losing their effectiveness. We have tried to circumvent the problem by reducing it into the fast computation of an optimum-path forest (OPF) in a graph derived from the training samples. In this forest, each class may be represented by multiple trees rooted at some representative samples. The forest is a classifier that assigns to a new sample the label of its most strongly connected root. The methodology has been successfully used with different graph topologies and learning techniques. In this work, we have focused on one of the supervised approaches, which has offered considerable advantages over Support Vector Machines and Artificial Neural Networks to handle large datasets. We propose (i) a new algorithm that speeds up classification and (ii) a solution to reduce the training set size with negligible effects on the accuracy of classification, therefore further increasing its efficiency. Experimental results show the improvements with respect to our previous approach and advantages over other existing methods, which make the new method a valuable contribution for large dataset analysis.