Image Form of the SECOM Dataset

Citation Author(s):
Jianwei
Zhao
Submitted by:
John Zhao
Last updated:
Fri, 03/13/2020 - 11:39
DOI:
10.21227/jkvr-n656
License:
0
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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.

Instructions: 

In the folder ``Classify_CNN'', files SECOM.xxxx.csv represent samples, in each of which, the first row can be ignored, and the remaining data is a matrix of size 24*20. The values indicate pixel values.

The labels is in file ``SECOM.label.csv''.

The folder ``FIGs'' contains the visualization of all samples.