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» A Learning Algorithm for Multiple Rule Trees
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BMCBI
2010
109views more  BMCBI 2010»
13 years 7 months ago
Predicting gene function using hierarchical multi-label decision tree ensembles
Background: S. cerevisiae, A. thaliana and M. musculus are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challe...
Leander Schietgat, Celine Vens, Jan Struyf, Hendri...
CORR
2002
Springer
91views Education» more  CORR 2002»
13 years 7 months ago
Data Engineering for the Analysis of Semiconductor Manufacturing Data
We have analyzed manufacturing data from several different semiconductor manufacturing plants, using decision tree induction software called Q-YIELD. The software generates rules ...
Peter D. Turney
ICIP
2010
IEEE
13 years 5 months ago
Building Emerging Pattern (EP) Random forest for recognition
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
Liang Wang, Yizhou Wang, Debin Zhao
JMLR
2010
107views more  JMLR 2010»
13 years 2 months ago
Learning Instance-Specific Predictive Models
This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algori...
Shyam Visweswaran, Gregory F. Cooper
EUROCOLT
1995
Springer
13 years 11 months ago
A decision-theoretic generalization of on-line learning and an application to boosting
k. The model we study can be interpreted as a broad, abstract extension of the well-studied on-line prediction model to a general decision-theoretic setting. We show that the multi...
Yoav Freund, Robert E. Schapire