Open AccessHigh density-focused uncertainty sampling for active learning over evolving stream data
Author(s) -
Dino Ienco,
Bernhard Pfahringer,
Indrė Žliobaitė
Publication year - 2014
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
Subject(s) - computer science , data stream mining , classifier (uml) , machine learning , data stream , artificial intelligence , sliding window protocol , benchmark (surveying) , labeled data , data mining , partition (number theory) , streaming data , window (computing) , mathematics , telecommunications , geodesy , combinatorics , geography , operating system