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TMM
2002
104views more  TMM 2002»
14 years 9 months ago
Spatial contextual classification and prediction models for mining geospatial data
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...
KDD
2009
ACM
173views Data Mining» more  KDD 2009»
15 years 10 months ago
The offset tree for learning with partial labels
We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
Alina Beygelzimer, John Langford
ECML
2006
Springer
15 years 1 months ago
Cost-Sensitive Decision Tree Learning for Forensic Classification
Abstract. In some learning settings, the cost of acquiring features for classification must be paid up front, before the classifier is evaluated. In this paper, we introduce the fo...
Jason V. Davis, Jungwoo Ha, Christopher J. Rossbac...
RIVF
2008
14 years 11 months ago
Unsupervised learning for image classification based on distribution of hierarchical feature tree
The classification image into one of several categories is a problem arisen naturally under a wide range of circumstances. In this paper, we present a novel unsupervised model for ...
Thach-Thao Duong, Joo-Hwee Lim, Hai-Quan Vu, Jean-...
GECCO
2010
Springer
169views Optimization» more  GECCO 2010»
15 years 1 months ago
Robust symbolic regression with affine arithmetic
We use affine arithmetic to improve both the performance and the robustness of genetic programming for symbolic regression. During evolution, we use affine arithmetic to analyze e...
Cassio Pennachin, Moshe Looks, João A. de V...