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PAKDD
2005
ACM
132views Data Mining» more  PAKDD 2005»
16 years 1 months ago
SETRED: Self-training with Editing
Self-training is a semi-supervised learning algorithm in which a learner keeps on labeling unlabeled examples and retraining itself on an enlarged labeled training set. Since the s...
Ming Li, Zhi-Hua Zhou
CASDMKM
2004
Springer
131views Data Mining» more  CASDMKM 2004»
16 years 27 days ago
XML-Based Schemes for Business Project Portfolio Selection
Abstract. Many methodologies have been introduced to deal with project portfolio selection problem including some techniques that help to evaluate individual projects, or to select...
Jichang Dong, Kin Keung Lai, Shouyang Wang
PAKDD
2004
ACM
96views Data Mining» more  PAKDD 2004»
16 years 26 days ago
Spectral Energy Minimization for Semi-supervised Learning
The use of unlabeled data to aid classification is important as labeled data is often available in limited quantity. Instead of utilizing training samples directly into semi-super...
Chun Hung Li, Zhi-Li Wu
PAKDD
2004
ACM
113views Data Mining» more  PAKDD 2004»
16 years 26 days ago
Logistic Regression and Boosting for Labeled Bags of Instances
Abstract. In this paper we upgrade linear logistic regression and boosting to multi-instance data, where each example consists of a labeled bag of instances. This is done by connec...
Xin Xu, Eibe Frank
PKDD
2004
Springer
141views Data Mining» more  PKDD 2004»
16 years 26 days ago
Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach
In this paper we propose a novel spatial associative classifier method based on a multi-relational approach that takes spatial relations into account. Classification is driven by s...
Michelangelo Ceci, Annalisa Appice, Donato Malerba