banknote_authentication: Bank Note Authentication Data Set

In nonet: Weighted Average Ensemble without Training Labels

Description

Bank Note Authentication Data Set is used to show the functionality of nonet package. This Data Set has below attribute information as variance of Wavelet Transformed image (continuous), skewness of Wavelet Transformed image (continuous), curtosis of Wavelet Transformed image (continuous),entropy of image (continuous), class (integer).

Usage

data("banknote_authentication")

Format

A data frame with 1372 observations on the following 5 variables.

variance

a numeric vector

skewness

a numeric vector

curtosis

a numeric vector

entropy

a numeric vector

class

a numeric vector

Details

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

This DataSet is fetched from UCI Website. URL is https://archive.ics.uci.edu/ml/datasets/banknote+authentication

References

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

Examples

data(banknote_authentication)
dataframe <- data.frame(banknote_authentication)
head(dataframe)
str(banknote_authentication)

Example output

  variance skewness curtosis  entropy class
1  3.62160   8.6661  -2.8073 -0.44699     0
2  4.54590   8.1674  -2.4586 -1.46210     0
3  3.86600  -2.6383   1.9242  0.10645     0
4  3.45660   9.5228  -4.0112 -3.59440     0
5  0.32924  -4.4552   4.5718 -0.98880     0
6  4.36840   9.6718  -3.9606 -3.16250     0
'data.frame':	1372 obs. of  5 variables:
 $ variance: num  3.622 4.546 3.866 3.457 0.329 ...
 $ skewness: num  8.67 8.17 -2.64 9.52 -4.46 ...
 $ curtosis: num  -2.81 -2.46 1.92 -4.01 4.57 ...
 $ entropy : num  -0.447 -1.462 0.106 -3.594 -0.989 ...
 $ class   : int  0 0 0 0 0 0 0 0 0 0 ...

nonet documentation built on May 2, 2019, 1:31 p.m.