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:
A data frame containing the following variables:
Variance of the wavelet transformed image.
Skewness of the wavelet transformed image.
Curtosis of the wavelet transformed image.
Entropy of the image.
A factor indicating the authenticity of the banknote. The factor has two levels:
Indicates the banknote is not genuine.
Indicates the banknote is genuine.
data(banknote)A list with two components:
A data frame with 4 variables: variance, skewness,
curtosis, and entropy.
A factor with levels "inauthentic" and "authentic"
representing the banknote's authenticity.
Gillich, Eugen & Lohweg, Volker. (2010). Banknote Authentication.