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» Limits on Learning Machine Accuracy Imposed by Data Quality
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ICMLA
2008
14 years 11 months ago
Comprehensible Models for Predicting Molecular Interaction with Heart-Regulating Genes
When using machine learning for in silico modeling, the goal is normally to obtain highly accurate predictive models. Often, however, models should also bring insights into intere...
Cecilia Sönströd, Ulf Johansson, Ulf Nor...
80
Voted
BMCBI
2008
114views more  BMCBI 2008»
14 years 9 months ago
Combining classifiers for improved classification of proteins from sequence or structure
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...
62
Voted
ICML
2009
IEEE
15 years 10 months ago
Multi-assignment clustering for Boolean data
Conventional clustering methods typically assume that each data item belongs to a single cluster. This assumption does not hold in general. In order to overcome this limitation, w...
Andreas P. Streich, Mario Frank, David A. Basin, J...
76
Voted
ECML
1997
Springer
15 years 1 months ago
Global Data Analysis and the Fragmentation Problem in Decision Tree Induction
We investigate an inherent limitation of top-down decision tree induction in which the continuous partitioning of the instance space progressively lessens the statistical support o...
Ricardo Vilalta, Gunnar Blix, Larry A. Rendell
UAI
2000
14 years 11 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping