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» Data Mining: Machine Learning, Statistics, and Databases
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ICML
2008
IEEE
16 years 2 months ago
Learning to classify with missing and corrupted features
After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in the training data. Particularl...
Ofer Dekel, Ohad Shamir
156
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WINE
2005
Springer
268views Economy» more  WINE 2005»
15 years 6 months ago
Mining Stock Market Tendency Using GA-Based Support Vector Machines
In this study, a hybrid intelligent data mining methodology, genetic algorithm based support vector machine (GASVM) model, is proposed to explore stock market tendency. In this hyb...
Lean Yu, Shouyang Wang, Kin Keung Lai
SAC
2006
ACM
15 years 7 months ago
Discretization from data streams: applications to histograms and data mining
Abstract. In this paper we propose a new method to perform incremental discretization. The basic idea is to perform the task in two layers. The first layer receives the sequence o...
João Gama, Carlos Pinto
ICML
2000
IEEE
16 years 2 months ago
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...
Paul Komarek, Andrew W. Moore

Book
640views
17 years 10 days ago
Introduction to Pattern Recognition
"Pattern recognition techniques are concerned with the theory and algorithms of putting abstract objects, e.g., measurements made on physical objects, into categories. Typical...
Sargur Srihari