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BMCBI
2010
118views more  BMCBI 2010»
13 years 5 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
ECML
2004
Springer
13 years 11 months ago
SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
Rong Jin, Huan Liu
BMCBI
2008
136views more  BMCBI 2008»
13 years 5 months ago
A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model
Background: Bioactivity profiling using high-throughput in vitro assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also r...
Richard Judson, Fathi Elloumi, R. Woodrow Setzer, ...
IADIS
2003
13 years 7 months ago
Hypertext Classification: A Multiagent Model for Adaptive Learning Algorithm
The problem of hypertext classification deals with objects possessing more complex information structure than the plain text has. Present hypertext classification systems show the...
Stanislav Baglei
ICML
2002
IEEE
14 years 6 months ago
Cranking: Combining Rankings Using Conditional Probability Models on Permutations
A new approach to ensemble learning is introduced that takes ranking rather than classification as fundamental, leading to models on the symmetric group and its cosets. The approa...
Guy Lebanon, John D. Lafferty