Titlebook: Discovery Science; 14th International C Tapio Elomaa,Jaakko Hollmén,Heikki Mannila Conference proceedings 2011 Springer-Verlag GmbH Berlin

持久

Conference proceedings 20115 invited lectures were carefully revised and selected from 56 submissions. The papers cover a wide range including the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, as well as their application to knowledge discovery.

抗生素

HEPA-filter

Georgia K. Hinkley,Stephen M. Robertsives (Type I error). Our contribution in this paper is to extend the multiple hypothesis framework to be used in a generic data mining setting. We provide a method that provably controls the family-wise error rate (FWER, the probability of at least one false positive). We show the power of our solution on real data.

越自我

https://doi.org/10.1007/978-94-017-3175-1rect outcome of an entropy function used in measuring the encoding length of clusters and the second one is realized through our new encoding method. Experiments using synthetic and real data sets give promising results.

犬儒主义者

植物茂盛

LIKEN

0302-9743 national Conference on Discovery Science, DS 2011, held in Espoo, Finland, in October 2011 - co-located with ALT 2011, the 22nd International Conference on Algorithmic Learning Theory. The 24 revised full papers presented together with 5 invited lectures were carefully revised and selected from 56 s

音的强弱

The Lasting Debate on Human Rightsl successful algorithms have been proposed in recent years. We review some of the theoretical motivations for deep architectures, as well as some of their practical successes, and propose directions of investigations to address some of the remaining challenges.

赏心悦目

不如屎壳郎