Indonesian Journal of Electrical Engineering and Computer Science
Vol 12, No 5: May 2014

Based on Weighted Gauss-Newton Neural Network Algorithm for Uneven Forestry Information Text Classification

Yu Chen (Northeast Forestry University)
Liwei Xu (Northeast Forestry University)



Article Info

Publish Date
01 May 2014

Abstract

In order to deal with the problem of low categorization accuracy of minority class of the uneven forestry information text classification algorithm, this paper puts forward the uneven forestry information text classification algorithm based on weighted Gauss-Newton neural network, on the basis of weighted Gauss-Newton algorithm, the algorithm is proved via singular value decomposition principle. The experimental result shows that the algorithm has higher classification accuracy of majority class and minority class than algorithm of common classification. The algorithm expands a new method for the research on the uneven forestry information text classification algorithm. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.4388

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