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Image Form of the SECOM Dataset
- Citation Author(s):
- Submitted by:
- John Zhao
- Last updated:
- Fri, 03/13/2020 - 11:39
- DOI:
- 10.21227/jkvr-n656
- License:
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Abstract
The original dataset SECOM is obtained from the the UC Irvine Machine Learning Repository (https://archive.ics.uci.edu/ml/datasets/secom). Then, each
sample is transformed to an image, with each pixel representing a feature. Therefore, image processing mechanisms such as convolutionary neural networks can be utilized for classification.