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CVPR
2004
IEEE
14 years 9 months ago
Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
MICCAI
2008
Springer
14 years 8 months ago
Classification of Suspected Liver Metastases Using fMRI Images: A Machine Learning Approach
Abstract. This paper presents a machine-learning approach to the interactive classification of suspected liver metastases in fMRI images. The method uses fMRI-based statistical mod...
Moti Freiman, Yifat Edrei, Yehonatan Sela, Yitz...
BMCBI
2006
180views more  BMCBI 2006»
13 years 7 months ago
Building multiclass classifiers for remote homology detection and fold recognition
Motivation Protein remote homology prediction and fold recognition are central problems in computational biology. Supervised learning algorithms based on support vector machines a...
Huzefa Rangwala, George Karypis
ML
2000
ACM
244views Machine Learning» more  ML 2000»
13 years 7 months ago
Learnable Evolution Model: Evolutionary Processes Guided by Machine Learning
A new class of evolutionary computation processes is presented, called Learnable Evolution Model or LEM. In contrast to Darwinian-type evolution that relies on mutation, recombinat...
Ryszard S. Michalski
FGR
2000
IEEE
159views Biometrics» more  FGR 2000»
13 years 12 months ago
Gesture Modeling and Recognition Using Finite State Machines
This paper proposes a state based approach to gesture learning and recognition. Using spatial clustering and temporal alignment, each gesture is defined to be an ordered sequence ...
Pengyu Hong, Thomas S. Huang, Matthew Turk