Rescaling is possibly the most popular approach to cost-sensitive learning. This approach works by rescaling the classes according to their costs, and it can be realized in differ...
We present results from experiments in using several pitch representations for jazz-oriented musical tasks performed by a recurrent neural network. We have run experiments with se...
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
ct The REGNET Project aims to develop a formal information infrastructure for regulatory information management and compliance assistance. This paper discusses three components of ...
Shawn Kerrigan, Charles Heenan, Haoyi Wang, Kincho...