diversityForest (version 0.5.0)

zoo: Data on biological species

Description

This data set describes 101 different biological species using 16 simple attributes, where 15 of these are binary and one is metric (the number of legs). The outcome "mammal vs. other" (type) is binary.

Format

A data frame with 101 observations, 16 covariates and one binary outcome variable

Details

The variables are as follows:

• hair. factor. Presence of hairs (true = yes; false = no)

• feathers. factor. Presence of feathers (true = yes; false = no)

• eggs. factor. Does the species lay eggs? (true = yes; false = no)

• milk. factor. Does the species give milk? (true = yes; false = no)

• airborne. factor. Does the species fly? (true = yes; false = no)

• aquatic. factor. Does the species live in the water? (true = yes; false = no)

• predator. factor. Is the species a predator? (true = yes; false = no)

• toothed. factor. Presence of teeth (true = yes; false = no)

• backbone. factor. Presence of backbone (true = yes; false = no)

• breathes. factor. Does the species breathe with lungs? (true = yes; false = no)

• venomous. factor. Is the species venomous? (true = yes; false = no)

• fins. factor. Presence of fins (true = yes; false = no)

• legs. metric. Number of legs

• tail. factor. Presence of tail (true = yes; false = no)

• domestic. factor. Is the species domestic? (true = yes; false = no)

• catsize. factor. Is the species large? (true = yes; false = no)

• type. factor. Binary outcome variable - type of species ('mammal' vs. 'other')

The original openML dataset contains an additional variable animal, which is removed in this version of the data set. This variable provided the names of all species.

References

• Vanschoren, J., van Rijn, J. N., Bischl, B., Torgo, L. (2013). OpenML: networked science in machine learning. SIGKDD Explorations 15(2):49-60, <tools:::Rd_expr_doi("10.1145/2641190.2641198")>.

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

Examples

##' Load data:
data(zoo)

##' Numbers of observations in the two classes:
table(zoo$type)

##' Dimension of data:
dim(zoo)

##' First rows of data:
head(zoo)