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Models for Calculating Confidence Intervals for Neural Networks Ashutosh Nandeshwar
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Models for Calculating Confidence Intervals for Neural Networks
Ashutosh Nandeshwar
This books provides the methodology of analyzing existing models to calculate confidence intervals on the results of neural networks. The three techniques for determining confidence intervals determination were the non-linear regression, the bootstrapping estimation, and the maximum likelihood estimation. The neural network used the backpropagation algorithm with an input layer, one hidden layer and an output layer with one unit. The hidden layer had a logistic or binary sigmoidal activation function and the output layer had a linear activation function. These techniques were tested on various data sets with and without additional noise. The ranges and standard deviations of the coverage probabilities over 15 simulations for the three techniques were computed.
| メディア | 書籍 Paperback Book (ソフトカバーで背表紙を接着した本) |
| リリース済み | 2008年12月10日 |
| ISBN13 | 9783639105483 |
| 出版社 | VDM Verlag |
| ページ数 | 132 |
| 寸法 | 150 × 220 × 10 mm · 185 g |
| 言語 | 英語 ドイツ語 |