banknote2: Swiss banknote data (UCI version)

In bgreenwell/treemisc: Data Sets and Functions to Accompany "Tree-Based Methods for Statistical Learning in R"

Swiss banknote data (UCI version)

Description

Data were extracted from images that were taken from genuine class = 1 and forged class = 0 banknote-like specimens. For digitization, an industrial camera usually used for print inspection was used. The final images contained 400 x 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 transformation tools were used to extract features from the images.

Format

A data frame with 1372 rows and 5 variables.

Details

vow

Variance of the wavelet transformed image (continuous)

sow

Skewness of the wavelet transformed image (continuous)

kow

Kurtosis of the wavelet transformed image (continuous)

eoi

Entropy of the image (continuous)

class

Integer specifying whether or not the specimen was genuine (class = 1) or forged (class = 0).

Source

Dua, D. and Graff, C. (2019). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.

bgreenwell/treemisc documentation built on Oct. 26, 2022, 12:56 a.m.