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MICAI
2007
Springer
15 years 10 months ago
Weighted Instance-Based Learning Using Representative Intervals
Instance-based learning algorithms are widely used due to their capacity to approximate complex target functions; however, the performance of this kind of algorithms degrades signi...
Octavio Gómez, Eduardo F. Morales, Jes&uacu...
SDM
2007
SIAM
182views Data Mining» more  SDM 2007»
15 years 5 months ago
Distance Preserving Dimension Reduction for Manifold Learning
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
Hyunsoo Kim, Haesun Park, Hongyuan Zha
ICIC
2005
Springer
15 years 9 months ago
Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
In recent years, mining with imbalanced data sets receives more and more attentions in both theoretical and practical aspects. This paper introduces the importance of imbalanced da...
Hui Han, Wenyuan Wang, Binghuan Mao
PKDD
2000
Springer
100views Data Mining» more  PKDD 2000»
15 years 7 months ago
Learning Right Sized Belief Networks by Means of a Hybrid Methodology
Previous algoritms for the construction of belief networks structures from data are mainly based either on independence criteria or on scoring metrics. The aim of this paper is to ...
Silvia Acid, Luis M. de Campos
IBPRIA
2007
Springer
15 years 5 months ago
Automatic Learning of Conceptual Knowledge in Image Sequences for Human Behavior Interpretation
This work describes an approach for the interpretation and explanation of human behavior in image sequences, within the context of a Cognitive Vision System. The information source...
Pau Baiget, Carles Fernández Tena, F. Xavie...