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