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A review of feature selection techniques in bioinformatics
TLDR
Feature selection techniques have become an apparent need in many bioinformatics applications. Expand
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Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators
TLDR
We present crossover and mutation operators, developed to tackle the Travelling Salesman Problem with Genetic Algorithms with different representations such as: binary representation, path representation, adjacency representation, ordinal representation and matrix representation. Expand
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Structure Learning of Bayesian Networks by Genetic Algorithms: A Performance Analysis of Control Parameters
TLDR
We present a new approach to structure learning in the field of Bayesian networks. Expand
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Estimation of Distribution Algorithms
TLDR
Estimation of Distribution Algorithms for Partial Abductive Inference in Bayesian Networks . Expand
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New insights into the classification and nomenclature of cortical GABAergic interneurons
A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergicExpand
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A survey on multi‐output regression
TLDR
A survey on state‐of-the-art multi-output regression methods, that are categorized as problem transformation and algorithm adaptation methods, as well as open‐source software frameworks. Expand
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An empirical comparison of four initialization methods for the K-Means algorithm
TLDR
We aim to compare empirically four initialization methods for the K-Means algorithm: random, Forgy, MacQueen and Kaufman. Expand
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Bayesian Chain Classifiers for Multidimensional Classification
TLDR
We introduce a method for chaining binary Bayesian classifiers that combines the strengths of classifier chains and Bayesian networks for multidimensional classification. Expand
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Machine learning in bioinformatics
TLDR
This article reviews machine learning methods for bioinformatics, such as supervised classification, clustering and probabilistic graphical models for knowledge discovery. Expand
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