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https://github.com/abhiroy96/banknote-authentication-uci-dataset
https://github.com/abhiroy96/banknote-authentication-uci-dataset
ipynb-notebook knn-classification machine-learning random-forest svm-classifier
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/abhiroy96/banknote-authentication-uci-dataset
- Owner: AbhiRoy96
- License: mit
- Created: 2018-04-22T11:54:12.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2018-04-22T12:01:35.000Z (almost 7 years ago)
- Last Synced: 2024-11-13T08:42:09.998Z (3 months ago)
- Topics: ipynb-notebook, knn-classification, machine-learning, random-forest, svm-classifier
- Language: HTML
- Size: 167 KB
- Stars: 1
- Watchers: 2
- Forks: 13
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Banknote-Authentication-UCI-Dataset
## Abstract:
Data were extracted from images that were taken for the evaluation of an authentication procedure for banknotes. Click here to get the dataset https://archive.ics.uci.edu/ml/machine-learning-databases/00267/### Attribute Information
1. variance of Wavelet Transformed image (continuous)
2. skewness of Wavelet Transformed image (continuous)
3. curtosis of Wavelet Transformed image (continuous)
4. entropy of image (continuous)
5. class (integer)### Data Set Information
Data were extracted from images that were taken from genuine and forged banknote-like specimens. For digitization, an industrial camera usually used for print inspection was used. The final images have 400x 400 pixels. Due to the object lens and distance to the investigated object gray-scale pictures with a resolution of about 660 dpi were gained. Wavelet Transform tool were used to extract features from images.### Source
Owner of database: Volker Lohweg (University of Applied Sciences, Ostwestfalen-Lippe, volker.lohweg '@' hs-owl.de)
Donor of database: Helene Dörksen (University of Applied Sciences, Ostwestfalen-Lippe, helene.doerksen '@' hs-owl.de)
Date received: August, 2012