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» A Model of Inductive Bias Learning
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WWW
2007
ACM
14 years 8 months ago
Efficient training on biased minimax probability machine for imbalanced text classification
The Biased Minimax Probability Machine (BMPM) constructs a classifier which deals with the imbalanced learning tasks. In this paper, we propose a Second Order Cone Programming (SO...
Xiang Peng, Irwin King
ML
2000
ACM
157views Machine Learning» more  ML 2000»
13 years 7 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
ICML
2005
IEEE
14 years 8 months ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
SCESM
2006
ACM
269views Algorithms» more  SCESM 2006»
14 years 1 months ago
Inferring operational requirements from scenarios and goal models using inductive learning
Goal orientation is an increasingly recognised Requirements Engineering paradigm. However, integration of goal modelling with operational models remains an open area for which the...
Dalal Alrajeh, Alessandra Russo, Sebastián ...
ICDM
2008
IEEE
112views Data Mining» more  ICDM 2008»
14 years 1 months ago
Supervised Inductive Learning with Lotka-Volterra Derived Models
We present a classification algorithm built on our adaptation of the Generalized Lotka-Volterra model, well-known in mathematical ecology. The training algorithm itself consists ...
Karen Hovsepian, Peter Anselmo, Subhasish Mazumdar