Shuttle: Shuttle Dataset (Statlog version)

In mlbench: Machine Learning Benchmark Problems

Shuttle Dataset (Statlog version)

Description

The shuttle dataset contains 9 attributes all of which are numerical with the first one being time. The last column is the class with the following 7 levels: Rad.Flow, Fpv.Close, Fpv.Open, High, Bypass, Bpv.Close, Bpv.Open.

Approximately 80% of the data belongs to class 1. Therefore the default accuracy is about 80%. The aim here is to obtain an accuracy of 99 - 99.9%.

Usage

data("Shuttle", package = "mlbench")

Format

A data frame with 58,000 observations on 9 numerical independent variables and 1 target class.

Source

• Source: Jason Catlett of Basser Department of Computer Science; University of Sydney; N.S.W.; Australia.

These data have been taken from the UCI Repository Of Machine Learning Databases (Blake & Merz 1998) and were converted to R format by Evgenia Dimitriadou in the late 1990s.

The current version of the UC Irvine Machine Learning Repository Statlog Shuttle data set is available from \Sexpr[results=rd]{tools:::Rd_expr_doi("10.24432/C5WS31")}.

References

Blake, C.L. & Merz, C.J. (1998). UCI Repository of Machine Learning Databases. Irvine, CA: University of California, Irvine, Department of Information and Computer Science. Formerly available from ‘⁠http://www.ics.uci.edu/~mlearn/MLRepository.html⁠’.

Examples

data("Shuttle", package = "mlbench")
summary(Shuttle)

mlbench documentation built on May 29, 2024, 4:49 a.m.