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Results 11 - 20
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3,390
Feature selection for high-dimensional data: a fast correlation-based filter solution
- In: Proceedings of the 20th International Conferences on Machine Learning
, 2003
"... Feature selection, as a preprocessing step to machine learning, is effective in reducing di-mensionality, removing irrelevant data, in-creasing learning accuracy, and improving result comprehensibility. However, the re-cent increase of dimensionality of data poses a severe challenge to many existing ..."
Abstract
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Cited by 276 (12 self)
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existing feature selection methods with respect to efficiency and effectiveness. In this work, we intro-duce a novel concept, predominant correla-tion, and propose a fast filter method which can identify relevant features as well as re-dundancy among relevant features without pairwise correlation analysis
Combining pairwise sequence similarity and support vector machines for remote protein homology detection
- Proc. 6th Ann. Int. Conf. Computational Molecular Biology
, 2002
"... One key element in understanding the molecular machinery of the cell is to understand the structure and function of each protein encoded in the genome. A very successful means of inferring the structure or function of a previously unannotated protein is via sequence similarity with one or more prote ..."
Abstract
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Cited by 205 (20 self)
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: pairwise sequence comparison, homology, detection, support vector machines. 1.
Sequence Comparisons Using Multiple Sequences Detect Three Times as Many Remote . . .
, 1998
"... The sequences of related proteins can diverge beyond the point where their relationship can be recognised by pairwise sequence comparisons. In attempts to overcome this limitation, methods have been developed that use as a query, not a single sequence, but sets of related sequences or a representati ..."
Abstract
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Cited by 244 (16 self)
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The sequences of related proteins can diverge beyond the point where their relationship can be recognised by pairwise sequence comparisons. In attempts to overcome this limitation, methods have been developed that use as a query, not a single sequence, but sets of related sequences or a
An extension on ―statistical comparisons of classifiers over multiple data sets‖ for all pairwise comparisons
- Journal of Machine Learning Research
"... In a recently published paper in JMLR, Demˇsar (2006) recommends a set of non-parametric statistical tests and procedures which can be safely used for comparing the performance of classifiers over multiple data sets. After studying the paper, we realize that the paper correctly introduces the basic ..."
Abstract
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Cited by 159 (37 self)
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adjusted and comparable p-values in multiple comparison procedures.
An Efficient Constraint Handling Method for Genetic Algorithms
- Computer Methods in Applied Mechanics and Engineering
, 1998
"... Many real-world search and optimization problems involve inequality and/or equality constraints and are thus posed as constrained optimization problems. In trying to solve constrained optimization problems using genetic algorithms (GAs) or classical optimization methods, penalty function methods hav ..."
Abstract
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Cited by 246 (19 self)
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's population-based approach and ability to make pair-wise comparison in tournament selection operator are explo...
pairwise comparisons of
, 2009
"... KISSa: a strategy to build multiple sequence alignments from ..."
How well is enzyme function conserved as a function of pairwise sequence identity
- J. Mol. Biol
, 2003
"... Enzyme function conservation has been used to derive the threshold of sequence identity necessary to transfer function from a protein of known function to an unknown protein. Using pairwise sequence comparison, several studies suggested that when the sequence identity is above 40%, enzyme function i ..."
Abstract
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Cited by 127 (15 self)
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is well conserved. In contrast, Rost argued that because of database bias, the results from such simple pairwise comparisons might be misleading. Thus, by grouping enzyme sequences into families based on sequence similarity and selecting representative sequences for comparison, he showed that enzyme
When Can We Rank Well from Comparisons of O(n log n) Non-Actively Chosen Pairs?
, 2016
"... Abstract Ranking from pairwise comparisons is a ubiquitous problem and has been studied in disciplines ranging from statistics to operations research and from theoretical computer science to machine learning. Here we consider a general setting where outcomes of pairwise comparisons between items i ..."
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, but are considerably more general. We then give a new algorithm called low-rank pairwise ranking (LRPR) which provably learns a good ranking from comparisons of only O(n log n) randomly chosen comparisons under such low-rank models. Our algorithm and analysis make use of tools from the theory of low-rank matrix
Label Ranking by Learning Pairwise Preferences
"... Preference learning is an emerging topic that appears in different guises in the recent literature. This work focuses on a particular learning scenario called label ranking, where the problem is to learn a mapping from instances to rankings over a finite number of labels. Our approach for learning s ..."
Abstract
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Cited by 89 (20 self)
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such a mapping, called ranking by pairwise comparison (RPC), first induces a binary preference relation from suitable training data using a natural extension of pairwise classification. A ranking is then derived from the preference relation thus obtained by means of a ranking procedure, whereby different
Results 11 - 20
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3,390
