Published July 27, 2017
| Version v1
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RAIN Journal-ANNSVM: A Novel Method for Graph-Type Classification by Utilization of Fourier Transformation, Wavelet Transformation, and Hough Transformation-Figure 4. Processes of all experiments:
Authors/Creators
- 1. Graduate School, Shibaura Institute of Technology, Tokyo, Japan
- 2. Information Science and Engineering, Shibaura Institute of Technology, Tokyo, Japan
Description
In this study, accuracy values of each dataset showed the performance of each method. These values represent are the proportion of the total number of predictions that were correctly classified. Initially, we classified training instances into three classes, with approximately 300 images per class. The graphs had been selectively gathered from the Web. We manually normalized the collected images by eliminating unused areas, such as unnecessary text. Moreover, we evaluated the experiments with 10 folds cross-validation because such an approach can mitigate the problem of over-fitting.
Notes
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Figure 4. Processes of all experiments.JPG
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