. Vice-Chair Prof. A. Aamodt, NUST, N-7491 Trondheim, Norway, email: . Secretary Dr. Nicolas Bredeche, Université Paris-Sud, 91405 Orsay, France, email: . Aim To study and develop theory and techniques for machine learning and data mining. Scope The scope of the Working Group’s activities includes (but is not restricted to) the following:    Association Rules Classification Rules Decision Trees    Case-Based Reasoning    Genetic Algorithms    Inductive Logic Programming    Neural Nets    Instance Based Learning    Support Vector Machines    Bagging and Boosting    Feature Reduction    Supervised and Unsupervised Learning    Web and Text Mining    Mining of Images, Video etc.    Concept Learning    Bayesian Learning    Computational Learning Theory    Reinforcement Learning " /> WG 12.2 - Machine Learning and Data Mining Group (This is a closed group) . Vice-Chair Prof. A. Aamodt, NUST, N-7491 Trondheim, Norway, email: . Secretary Dr. Nicolas Bredeche, Université Paris-Sud, 91405 Orsay, France, email: . Aim To study and develop theory and techniques for machine learning and data mining. Scope The scope of the Working Group’s activities includes (but is not restricted to) the following:    Association Rules Classification Rules Decision Trees    Case-Based Reasoning    Genetic Algorithms    Inductive Logic Programming    Neural Nets    Instance Based Learning    Support Vector Machines    Bagging and Boosting    Feature Reduction    Supervised and Unsupervised Learning    Web and Text Mining    Mining of Images, Video etc.    Concept Learning    Bayesian Learning    Computational Learning Theory    Reinforcement Learning"/>
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WG 12.2 - Machine Learning and Data Mining

WG 12.2 - Machine Learning and Data Mining

 
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        WG 12.2 - Machine Learning and Data Mining
        • Officers Chair Prof Zhongzhi Shi, Chinese Academy of Sciences, Beijing 100080 China, email: . Vice-Chair Prof. A. Aamodt, NUST, N-7491 Trondheim, Norway, email: . Secretary Dr. Nicolas Bredeche, Université Paris-Sud, 91405 Orsay, France, email: . Aim To study and develop theory and techniques for machine learning and data mining. Scope The scope of the Working Group’s activities includes (but is not restricted to) the following:    Association Rules Classification Rules Decision Trees    Case-Based Reasoning    Genetic Algorithms    Inductive Logic Programming    Neural Nets    Instance Based Learning    Support Vector Machines    Bagging and Boosting    Feature Reduction    Supervised and Unsupervised Learning    Web and Text Mining    Mining of Images, Video etc.    Concept Learning    Bayesian Learning    Computational Learning Theory    Reinforcement Learning
        • Category
          TC12
        • Created
          Tuesday, 03 June 2014
        • Group admin
          Webmaster