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ICPR
2008
IEEE
14 years 1 months ago
Relevant pattern selection for subspace learning
In this paper, we propose a scheme to improve the performance of subspace learning by using a pattern(data) selection method as preprocessing. Generally, a training set for subspa...
Jin Hee Na, Seok Min Yun, Minsoo Kim, Jin Young Ch...
EMNLP
2008
13 years 8 months ago
Understanding the Value of Features for Coreference Resolution
In recent years there has been substantial work on the important problem of coreference resolution, most of which has concentrated on the development of new models and algorithmic...
Eric Bengtson, Dan Roth
AI
2004
Springer
13 years 7 months ago
A selective sampling approach to active feature selection
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
Huan Liu, Hiroshi Motoda, Lei Yu
ICDM
2008
IEEE
110views Data Mining» more  ICDM 2008»
14 years 1 months ago
Start Globally, Optimize Locally, Predict Globally: Improving Performance on Imbalanced Data
Class imbalance is a ubiquitous problem in supervised learning and has gained wide-scale attention in the literature. Perhaps the most prevalent solution is to apply sampling to t...
David A. Cieslak, Nitesh V. Chawla
AAAI
2011
12 years 7 months ago
Improving Semi-Supervised Support Vector Machines Through Unlabeled Instances Selection
Semi-supervised support vector machines (S3VMs) are a kind of popular approaches which try to improve learning performance by exploiting unlabeled data. Though S3VMs have been fou...
Yu-Feng Li, Zhi-Hua Zhou