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» Machine Learning with Data Dependent Hypothesis Classes
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MLDM
2007
Springer
14 years 2 months ago
Nonlinear Feature Selection by Relevance Feature Vector Machine
Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...
Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yo...
ICML
2009
IEEE
14 years 3 months ago
Fast evolutionary maximum margin clustering
The maximum margin clustering approach is a recently proposed extension of the concept of support vector machines to the clustering problem. Briefly stated, it aims at finding a...
Fabian Gieseke, Tapio Pahikkala, Oliver Kramer
IADIS
2009
13 years 6 months ago
Proposed framework for data mining in e-learning: The case of open e-class
Web-based learning environments are extensively used nowadays. These environments maintain and produce vast amounts of data. Such vastness lead to the application of data mining t...
Ioannis Kazanidis, Stavros Valsamidis, Theodosios ...
SDM
2010
SIAM
226views Data Mining» more  SDM 2010»
13 years 10 months ago
Two-View Transductive Support Vector Machines
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam...
Guangxia Li, Steven C. H. Hoi, Kuiyu Chang
MLDM
2005
Springer
14 years 2 months ago
Statistical Supports for Frequent Itemsets on Data Streams
Abstract. A statistical technique is developed for estimating the support of itemsets on data streams, regardless of the size of the data stored. This technique, which is computati...
Pierre-Alain Laur, Jean-Emile Symphor, Richard Noc...