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Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection Within Fruit Juice Classification
(Hindawi, 2013-10-21)
[Abstract] Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines ...
Applied Computational Techniques on Schizophrenia Using Genetic Mutations
(Bentham, 2013-03-01)
[Abstract] Schizophrenia is a complex disease, with both genetic and environmental influence. Machine learning techniques can be used to associate different genetic variations at different genes with a (schizophrenic or ...
Kernel-Based Feature Selection Techniques for Transport Proteins Based on Star Graph Topological Indices
(Bentham, 2013)
[Abstract] The transport of the molecules inside cells is a very important topic, especially in Drug Metabolism. The experimental testing of the new proteins for the transporter molecular function is expensive and inefficient ...
Evolutionary Computation and QSAR Research
(Bentham Science, 2013)
[Abstract] The successful high throughput screening of molecule libraries for a specific biological property is one of the main improvements in drug discovery. The virtual molecular filtering and screening relies greatly ...
Exploring Patterns of Epigenetic Information With Data Mining Techniques
(Bentham, 2013-02-01)
[Abstract] Data mining, a part of the Knowledge Discovery in Databases process (KDD), is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database ...
Classification of Signals by Means of Genetic Programming
(Springer, 2013-03-30)
[Abstract] This paper describes a new technique for signal classification by means of Genetic Programming (GP). The novelty of this technique is that no prior knowledge of the signals is needed to extract the features. ...
Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal Classification
(Inderscience, 2013)
[Abstract] ANNs are one of the most successful learning systems. For this
reason, many techniques have been
published that allow the obtaining of
feed-forward networks. However, fe
w ...