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.

Dataset Files

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[1] Jianwei Zhao, "Image Form of the SECOM Dataset", IEEE Dataport, 2020. [Online]. Available: http://dx.doi.org/10.21227/jkvr-n656. Accessed: Feb. 29, 2024.
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doi = {10.21227/jkvr-n656},
url = {http://dx.doi.org/10.21227/jkvr-n656},
author = {Jianwei Zhao },
publisher = {IEEE Dataport},
title = {Image Form of the SECOM Dataset},
year = {2020} }
TY - DATA
T1 - Image Form of the SECOM Dataset
AU - Jianwei Zhao
PY - 2020
PB - IEEE Dataport
UR - 10.21227/jkvr-n656
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Jianwei Zhao. (2020). Image Form of the SECOM Dataset. IEEE Dataport. http://dx.doi.org/10.21227/jkvr-n656
Jianwei Zhao, 2020. Image Form of the SECOM Dataset. Available at: http://dx.doi.org/10.21227/jkvr-n656.
Jianwei Zhao. (2020). "Image Form of the SECOM Dataset." Web.
1. Jianwei Zhao. Image Form of the SECOM Dataset [Internet]. IEEE Dataport; 2020. Available from : http://dx.doi.org/10.21227/jkvr-n656
Jianwei Zhao. "Image Form of the SECOM Dataset." doi: 10.21227/jkvr-n656