Abstract. Protein membership prediction is a fundamental task to retrieve information for unknown or unidentified sequences. When support vector machines (SVMs) are associated with...
We study algorithms for clustering data that were recently proposed by Balcan, Blum and Gupta in SODA’09 [4] and that have already given rise to two follow-up papers. The input f...
—Extensive research has been conducted on top of online social networks (OSNs), while little attention has been paid to the data collection process. Due to the large scale of OSN...
There are many machine learning algorithms currently available. In the 21st century, the problem no longer lies in writing the learner, but in choosing which learners to run on a ...
Proceedings of IEEE Data Mining, IEEE Press, pp. 581-584, 2002. We describe an interactive way to generate a set of clusters for a given data set. The clustering is done by constr...
Michael R. Berthold, Bernd Wiswedel, David E. Patt...
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simple...
A speaker model in speaker recognition system is to be trained from a large data set gathered in multiple sessions. Large data set requires large amount of memory and computation, ...
A new method for ensemble generation is presented. It is based on grouping the attributes in dierent subgroups, and to apply, for each group, an axis rotation, using Principal Com...
An important task in machine learning is determining which learning algorithm works best for a given data set. When the amount of data is small the same data needs to be used repea...
With the exploding volume of microarray experiments comes increasing interest in mining repositories of such data. Meaningfully combining results from varied experiments on an equ...