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» An Application of Boosting to Graph Classification
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NIPS
2004
13 years 6 months ago
An Application of Boosting to Graph Classification
This paper presents an application of Boosting for classifying labeled graphs, general structures for modeling a number of real-world data, such as chemical compounds, natural lan...
Taku Kudo, Eisaku Maeda, Yuji Matsumoto
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 2 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu
KDD
2010
ACM
197views Data Mining» more  KDD 2010»
13 years 2 months ago
Semi-supervised feature selection for graph classification
The problem of graph classification has attracted great interest in the last decade. Current research on graph classification assumes the existence of large amounts of labeled tra...
Xiangnan Kong, Philip S. Yu
PRL
2006
146views more  PRL 2006»
13 years 4 months ago
Boosting the distance estimation: Application to the K-Nearest Neighbor Classifier
In this work we introduce a new distance estimation technique by boosting and we apply it to the K-Nearest Neighbor Classifier (KNN). Instead of applying AdaBoost to a typical cla...
Jaume Amores, Nicu Sebe, Petia Radeva