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» Using Machine Learning Techniques to Interpret WH-questions
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ICML
2006
IEEE
16 years 2 months ago
Iterative RELIEF for feature weighting
RELIEF is considered one of the most successful algorithms for assessing the quality of features. In this paper, we propose a set of new feature weighting algorithms that perform s...
Yijun Sun, Jian Li
ACL
1998
15 years 2 months ago
Experiments with Learning Parsing Heuristics
Any large language processing software relies in its operation on heuristic decisions concerning the strategy of processing. These decisions are usually "hard-wired" int...
Sylvain Delisle, Sylvain Létourneau, Stan M...
BMCBI
2006
183views more  BMCBI 2006»
15 years 1 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
15 years 7 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
ICML
2008
IEEE
16 years 2 months ago
Detecting statistical interactions with additive groves of trees
Discovering additive structure is an important step towards understanding a complex multi-dimensional function because it allows the function to be expressed as the sum of lower-d...
Daria Sorokina, Rich Caruana, Mirek Riedewald, Dan...