We present a new family of linear time algorithms based on sufficient statistics for string comparison with mismatches under the string kernels framework. Our algorithms improve t...
In this paper we study the problem of constructing accurate decision tree models from data streams. Data streams are incremental tasks that require incremental, online, and any-ti...
In this paper, we propose an efficient algorithm, called MQSchange (changes of Music Query Streams), to detect the changes of maximal melody structures in user-centered music quer...
Many applications make use of named entity classification. Machine learning is the preferred technique adopted for many named entity classification methods where the choice of feat...
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...