The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Incremental Approach to Classification Learning
Abstract
An approach to incremental classification learning is proposed. Classification learning is based on approximation of a given partitioning of objects into disjointed blocks in multivalued space of attributes. Good approximation is defined in the form of good maximally redundant classification test or good formal concept. A concept of classification context is introduced. Four situations of incremental modification of classification context are considered: adding and deleting objects and adding and deleting values of attributes. Algorithms of changing good concepts in these incremental situations are given and proven.
Related Content
Elisha Mupaikwa, Preksha Yadav.
© 2025.
28 pages.
|
Christos Papademetriou, Konstantina Ragazou, Alexandros Garefalakis, Sofia Anastasiadou.
© 2025.
26 pages.
|
Kavitha R. Gowda, Joseph Varghese Kureethara, Sunanda Vincent Jaiwant.
© 2025.
24 pages.
|
Thriveni Kumari Karlapudi.
© 2025.
30 pages.
|
Bhupinder Singh, Christian Kaunert, Kamalesh Ravesangar.
© 2025.
26 pages.
|
Mithun Bhowmick, Sourajyoti Goswami, Rideb Chakraborty, Pratibha Bhowmick, Souvik Kumar Nandy, Naureen Afrose, Shailesh M. Kewatkar.
© 2025.
32 pages.
|
Madhusudan Narayan, Kaushlendra Pathak, Pooja Shukla.
© 2025.
24 pages.
|
|
|