Sayed-Mouchaweh, Moamar.
Learning from Data Streams in Dynamic Environments [electronic resource] / by Moamar Sayed-Mouchaweh. - VIII, 75 p. 44 illus., 43 illus. in color. online resource. - SpringerBriefs in Applied Sciences and Technology, 2191-530X . - SpringerBriefs in Applied Sciences and Technology, .
Introduction to learning -- Learning in dynamic environment -- Handling concept drift -- Summary and final comments.
This book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust its parameters according to the changes in their environments. Also presents the problem of learning in non-stationary environments, its interests, its applications and challenges and studies the complementarities and the links between the different methods and techniques of learning in evolving and non-stationary environments.
9783319256672
10.1007/978-3-319-25667-2 doi
Engineering.
Artificial intelligence.
Computational intelligence.
Electrical engineering.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Communications Engineering, Networks.
Q342
006.3
Learning from Data Streams in Dynamic Environments [electronic resource] / by Moamar Sayed-Mouchaweh. - VIII, 75 p. 44 illus., 43 illus. in color. online resource. - SpringerBriefs in Applied Sciences and Technology, 2191-530X . - SpringerBriefs in Applied Sciences and Technology, .
Introduction to learning -- Learning in dynamic environment -- Handling concept drift -- Summary and final comments.
This book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust its parameters according to the changes in their environments. Also presents the problem of learning in non-stationary environments, its interests, its applications and challenges and studies the complementarities and the links between the different methods and techniques of learning in evolving and non-stationary environments.
9783319256672
10.1007/978-3-319-25667-2 doi
Engineering.
Artificial intelligence.
Computational intelligence.
Electrical engineering.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Communications Engineering, Networks.
Q342
006.3