Difference between revisions of "Publications:Almost Linear Biobasis Function Neural Networks"
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| − | |Name=You, Liwen | + | |Name=You, Liwen (liyo) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), Intelligenta system (IS-lab) (3941));Rögnvaldsson, Thorsteinn (denni) (0000-0001-5163-2997) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), Intelligenta system (IS-lab) (3941)) |
|Title=Almost Linear Biobasis Function Neural Networks | |Title=Almost Linear Biobasis Function Neural Networks | ||
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| Title | Almost Linear Biobasis Function Neural Networks |
|---|---|
| Author | |
| Year | 2007 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | The 2007 International Joint Conference on Neural Networks : IJCNN 2007 conference proceedings : August 12-17, 2007, Resaissance Orlando Resort, Orlando, Florida, USA |
| Conference | The 2007 International Joint Conference on Neural Networks |
| DOI | http://dx.doi.org/10.1109/IJCNN.2007.4371226 |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:327085 |
| Abstract | 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. |
