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» Large-Scale Data Analysis Using Heuristic Methods
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WWW
2011
ACM
14 years 12 months ago
Parallel boosted regression trees for web search ranking
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
131
Voted
EVOW
2004
Springer
15 years 10 months ago
Evolutionary Search of Thresholds for Robust Feature Set Selection: Application to the Analysis of Microarray Data
Abstract. We deal with two important problems in pattern recognition that arise in the analysis of large datasets. While most feature subset selection methods use statistical techn...
Carlos Cotta, Christian Sloper, Pablo Moscato
IJCAI
2007
15 years 6 months ago
Parametric Kernels for Sequence Data Analysis
A key challenge in applying kernel-based methods for discriminative learning is to identify a suitable kernel given a problem domain. Many methods instead transform the input data...
Young-In Shin, Donald S. Fussell
161
Voted
DAS
2008
Springer
15 years 6 months ago
A Fast Preprocessing Method for Table Boundary Detection: Narrowing Down the Sparse Lines Using Solely Coordinate Information
As the rapid growth of PDF document in digital libraries, recognizing the document structure and detecting specific document components are useful for document storage, classifica...
Ying Liu, Prasenjit Mitra, C. Lee Giles
ISCI
2008
124views more  ISCI 2008»
15 years 5 months ago
A weighted rough set based method developed for class imbalance learning
In this paper, we introduce weights into Pawlak rough set model to balance the class distribution of a data set and develop a weighted rough set based method to deal with the clas...
Jinfu Liu, Qinghua Hu, Daren Yu