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ML
2006
ACM
142views Machine Learning» more  ML 2006»
14 years 9 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
JDWM
2007
122views more  JDWM 2007»
14 years 9 months ago
A Hyper-Heuristic for Descriptive Rule Induction
Rule induction from examples is a machine learning technique that finds rules of the form condition → class, where condition and class are logic expressions of the form variable...
Tho Hoan Pham, Tu Bao Ho
85
Voted
BMCBI
2004
196views more  BMCBI 2004»
14 years 9 months ago
MUSCLE: a multiple sequence alignment method with reduced time and space complexity
Background: In a previous paper, we introduced MUSCLE, a new program for creating multiple alignments of protein sequences, giving a brief summary of the algorithm and showing MUS...
Robert C. Edgar
BMCBI
2007
106views more  BMCBI 2007»
14 years 9 months ago
Improved classification accuracy in 1- and 2-dimensional NMR metabolomics data using the variance stabilising generalised logari
Background: Classifying nuclear magnetic resonance (NMR) spectra is a crucial step in many metabolomics experiments. Since several multivariate classification techniques depend up...
Helen M. Parsons, Christian Ludwig, Ulrich L. G&uu...
AI
2002
Springer
14 years 9 months ago
Improving heuristic mini-max search by supervised learning
This article surveys three techniques for enhancing heuristic game-tree search pioneered in the author's Othello program Logistello, which dominated the computer Othello scen...
Michael Buro