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» A Bayesian Metric for Evaluating Machine Learning Algorithms
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ICPR
2006
IEEE
15 years 11 months ago
Bayesian Imitation of Human Behavior in Interactive Computer Games
Modern interactive computer games provide the ability to objectively record complex human behavior, offering a variety of interesting challenges to the pattern-recognition communi...
Bernard Gorman, Christian Bauckhage, Christian Thu...
ICDM
2010
IEEE
134views Data Mining» more  ICDM 2010»
14 years 7 months ago
Consequences of Variability in Classifier Performance Estimates
The prevailing approach to evaluating classifiers in the machine learning community involves comparing the performance of several algorithms over a series of usually unrelated data...
Troy Raeder, T. Ryan Hoens, Nitesh V. Chawla
NIPS
2004
14 years 11 months ago
Object Classification from a Single Example Utilizing Class Relevance Metrics
We describe a framework for learning an object classifier from a single example. This goal is achieved by emphasizing the relevant dimensions for classification using available ex...
Michael Fink 0002
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
15 years 10 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
ECML
1993
Springer
15 years 1 months ago
SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes based Concepts
This paper describes a genetic learning system called SIA, which learns attributes based rules from a set of preclassified examples. Examples may be described with a variable numbe...
Gilles Venturini