Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
Combining multiple information sources, typically from several data streams is a very promising approach, both in experiments and to some extend in various real-life applications. ...
We analyze skewing, an approach that has been empirically observed to enable greedy decision tree learners to learn "difficult" Boolean functions, such as parity, in the...
Bernard Rosell, Lisa Hellerstein, Soumya Ray, Davi...
In recent years, many algorithms for the Web have been developed that work with information units distinct from individual web pages. These include segments of web pages or aggreg...
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...