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ICML
2010
IEEE
15 years 5 months ago
Causal filter selection in microarray data
The importance of bringing causality into play when designing feature selection methods is more and more acknowledged in the machine learning community. This paper proposes a filt...
Gianluca Bontempi, Patrick Emmanuel Meyer
ICDM
2006
IEEE
131views Data Mining» more  ICDM 2006»
15 years 10 months ago
Dimension Reduction for Supervised Ordering
Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results and best-seller lists. Techniques for processing such ordinal d...
Toshihiro Kamishima, Shotaro Akaho
IJON
2010
152views more  IJON 2010»
15 years 2 months ago
Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data
Due to the tremendous increase of electronic information with respect to the size of data sets as well as their dimension, dimension reduction and visualization of high-dimensiona...
Kerstin Bunte, Barbara Hammer, Axel Wismüller...
114
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DAARC
2007
Springer
86views Algorithms» more  DAARC 2007»
15 years 10 months ago
Evaluating Hybrid Versus Data-Driven Coreference Resolution
Abstract. In this paper, we present a systematic evaluation of a hybrid approach of combined rule-based filtering and machine learning to Dutch coreference resolution. Through the...
Iris Hendrickx, Véronique Hoste, Walter Dae...
ISMB
2000
15 years 5 months ago
A Probabilistic Learning Approach to Whole-Genome Operon Prediction
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...