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Almost Linear Biobasis Function Neural Networks

You, Liwen, Rögnvaldsson, Thorsteinn

Konferensbidrag (Övrigt vetenskapligt)


An analysis of biobasis function neural networks is presented, which shows that the similarity metric used is a linear function and that bio-basis function neural networks therefore often end up being just linear classifiers in high dimensional spaces. This is a consequence of four things: the linearity of the distance measure, the normalization of the distance measure, the recommended default values of the parameters, and that biological data sets are sparse.

Nyckelord: biobasis function neural networks; biological data set; biology computing; data analysis; distance measure linearity; distance measure normalization; linear classifiers; linear function; neural nets; pattern classification; similarity metric

Citera: You, Liwen & Rögnvaldsson, Thorsteinn, Almost Linear Biobasis Function Neural Networks, The 2007 International Joint Conference on Neural Networks : IJCNN 2007 conference proceedings : August 12-17, 2007, Resaissance Orlando Resort, Orlando, Florida, USA., s. 1774-1778, 2007http://hh.diva-portal.org/smash/get/diva2:327085/FULLTEXT01.pdf