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| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| Parent folder | |||
| miRimbal_v02r1b.zip | 2018-11-05 | 42.0 MB | |
| README.txt | 2018-11-01 | 1.1 kB | |
| Totals: 2 Items | 42.0 MB | 0 | |
This is a distribution of the source code used in: "Deep neural architectures for highly imbalanced data in bioinformatics" L. A. Bugnon, C. Yones, D. H. Milone and G. Stegmayer* sinc(i) - http://sinc.unl.edu.ar License ======= This code can be used, modified or distributed for academic purposes under GNU GPL. Please feel free to contact with any issue, comment or suggestion. Dependencies ============ This source code requires a few standard libraries, which are open and free to use. Setup instructions for the following packages can be found here: https://wiki.python.org/moin/BeginnersGuide/Download. The recommended package versions are in brackets. Requirements: - Python [2.7.13 or 3.5.4] - Matlab: 2016 - sompy: SOM library for python Python packages: - scipy [0.18.1] Usage ===== To run the tests, execute the Matlab script "main.m" from the root folder. By default, the DeepBN classifier is tested. To choose another classifier, simply change the variable "modelname" with "svm", "mlp", "deepbn", "deepsom", "desom" or "deesom". The results will be shown on the command line and saved in a log file in the folder "log".