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» Nested Ordered Sets and their Use for Data Modelling
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GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 1 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
KDD
2002
ACM
155views Data Mining» more  KDD 2002»
16 years 28 days ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui
SDM
2010
SIAM
184views Data Mining» more  SDM 2010»
15 years 2 months ago
A Robust Decision Tree Algorithm for Imbalanced Data Sets
We propose a new decision tree algorithm, Class Confidence Proportion Decision Tree (CCPDT), which is robust and insensitive to class distribution and generates rules which are st...
Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V...
HPTS
1993
147views Database» more  HPTS 1993»
15 years 4 months ago
Generic Action Support for Distributed, Cooperative Applications
Elements of transaction processing become more and more accepted as a base for general purpose distributed computing.We have developed an action concept with an extended functiona...
Edgar Nett, Michael Mock
PAMI
2008
160views more  PAMI 2008»
15 years 14 days ago
Motion Segmentation and Depth Ordering Using an Occlusion Detector
We present a novel method for motion segmentation and depth ordering from a video sequence in general motion. We first compute motion segmentation based on differential properties ...
Doron Feldman, Daphna Weinshall