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Titlebook: Bioinformatics and Biomedical Engineering; 5th International Wo Ignacio Rojas,Francisco Ortu?o Conference proceedings 2017 Springer Interna

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21#
發(fā)表于 2025-3-25 04:37:47 | 只看該作者
0302-9743 nference on Bioinformatics and Biomedical Engineering, IWBBIO 2017, held in Granada, Spain, in April 2017..The 122 papers presented were carefully reviewed and selected from 309 submissions. The scope of the conference spans the following areas: advances in computational intelligence for critical ca
22#
發(fā)表于 2025-3-25 10:49:31 | 只看該作者
23#
發(fā)表于 2025-3-25 13:57:49 | 只看該作者
24#
發(fā)表于 2025-3-25 19:02:35 | 只看該作者
25#
發(fā)表于 2025-3-25 20:14:50 | 只看該作者
A Meta-Review of Feature Selection Techniques in the Context of Microarray Data for microarray data in order to understand their underlying classification of methods. Finally, on this base, we propose an extended taxonomy for categorizing feature selection techniques and use it to classify the main methods presented in the selected reviews.
26#
發(fā)表于 2025-3-26 01:34:57 | 只看該作者
Colormetric Experiments on Aquatic Organismsevaluation, is of the concern of this article. Various fish species were subjected of the test. We performed transformations to other color space and using multivariate data statistics, namely principal component analysis, the relevant color space is seleted. The presented software solutions are available at ..
27#
發(fā)表于 2025-3-26 08:16:17 | 只看該作者
28#
發(fā)表于 2025-3-26 09:46:24 | 只看該作者
Markus Oestreich,Oliver Rombergional Intelligence and Machine Learning methods have already shown their usefulness in tackling problems in the area. This brief paper aims to be an introduction to the use of such methods in critical care.
29#
發(fā)表于 2025-3-26 16:24:51 | 只看該作者
30#
發(fā)表于 2025-3-26 18:20:22 | 只看該作者
Markus Oestreich,Oliver Rombergnd every method gives different insights into the data. The greedy style forward selection usually overfits and shows the largest difference between training and testing data, the PLS and PCA perform worse on the artificial data, but better for the ultrasound data.
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