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» On Combining Classifiers
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CVPR
2006
IEEE
15 years 3 days ago
A Generative-Discriminative Hybrid Method for Multi-View Object Detection
We present a novel discriminative-generative hybrid approach in this paper, with emphasis on application in multiview object detection. Our method includes a novel generative mode...
DongQing Zhang, Shih-Fu Chang
ESANN
2004
13 years 11 months ago
Face Recognition Using Recurrent High-Order Associative Memories
A novel face recognition approach is proposed, based on the use of compressed discriminative features and recurrent neural classifiers. Low-dimensional feature vectors are extract...
Iulian B. Ciocoiu
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
14 years 1 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
IJCNN
2007
IEEE
14 years 4 months ago
Random Feature Subset Selection for Analysis of Data with Missing Features
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Joseph DePasquale, Robi Polikar
MDAI
2005
Springer
14 years 3 months ago
Cancer Prediction Using Diversity-Based Ensemble Genetic Programming
Combining a set of classifiers has often been exploited to improve the classification performance. Accurate as well as diverse base classifiers are prerequisite to construct a good...
Jin-Hyuk Hong, Sung-Bae Cho