banknote {SLmetrics} | R Documentation |
Banknote authentication dataset
Description
This dataset contains features extracted from the wavelet transform of banknote images, which are used to classify banknotes as authentic or inauthentic. The data originates from the UCI Machine Learning Repository.
The data is provided as a list with two components:
- features
A data frame containing the following variables:
- variance
Variance of the wavelet transformed image.
- skewness
Skewness of the wavelet transformed image.
- curtosis
Curtosis of the wavelet transformed image.
- entropy
Entropy of the image.
- target
A factor indicating the authenticity of the banknote. The factor has two levels:
- inauthentic
Indicates the banknote is not genuine.
- authentic
Indicates the banknote is genuine.
Usage
data(banknote)
Format
A list with two components:
- features
A data frame with 4 variables:
variance
,skewness
,curtosis
, andentropy
.- target
A factor with levels
"inauthentic"
and"authentic"
representing the banknote's authenticity.
References
Gillich, Eugen & Lohweg, Volker. (2010). Banknote Authentication.