Description Usage Format Details Source References Examples

Dataset used as training data in the study cited below. These are the first 11,340 observations, out of 581012, in the dataset on the UCI site. Forest cover type is recorded, together with information on physical geographical variables that may account for the forest cover type.

1 |

A data frame with 11318 observations on the following 55 variables.

`V1`

a numeric vector

`V2`

a numeric vector

`V3`

a numeric vector

`V4`

a numeric vector

`V5`

a numeric vector

`V6`

a numeric vector

`V7`

a numeric vector

`V8`

a numeric vector

`V9`

a numeric vector

`V10`

a numeric vector

`V11`

a numeric vector

`V12`

a numeric vector

`V13`

a numeric vector

`V14`

a numeric vector

`V15`

a numeric vector

`V16`

a numeric vector

`V17`

a numeric vector

`V18`

a numeric vector

`V19`

a numeric vector

`V20`

a numeric vector

`V21`

a numeric vector

`V22`

a numeric vector

`V23`

a numeric vector

`V24`

a numeric vector

`V25`

a numeric vector

`V26`

a numeric vector

`V27`

a numeric vector

`V28`

a numeric vector

`V29`

a numeric vector

`V30`

a numeric vector

`V31`

a numeric vector

`V32`

a numeric vector

`V33`

a numeric vector

`V34`

a numeric vector

`V35`

a numeric vector

`V36`

a numeric vector

`V37`

a numeric vector

`V38`

a numeric vector

`V39`

a numeric vector

`V40`

a numeric vector

`V41`

a numeric vector

`V42`

a numeric vector

`V43`

a numeric vector

`V44`

a numeric vector

`V45`

a numeric vector

`V46`

a numeric vector

`V47`

a numeric vector

`V48`

a numeric vector

`V49`

a numeric vector

`V50`

a numeric vector

`V51`

a numeric vector

`V52`

a numeric vector

`V53`

a numeric vector

`V54`

a numeric vector

`V55`

a numeric vector

For details, see http://kdd.ics.uci.edu/databases/covertype/covertype.data.html

For details, see http://kdd.ics.uci.edu/databases/covertype/covertype.data.html. Note the omission of any information on geographical location. Distance through the data seems however to be, in part, a proxy for geographical location.

http://kdd.ics.uci.edu/databases/covertype/covertype.html

Blackard, Jock A. 1998. "Comparison of Neural Networks and Discriminant Analysis in Predicting Forest Cover Types." Ph.D. dissertation. Department of Forest Sciences. Colorado State University. Fort Collins, Colorado.

1 |

DAAGxtras documentation built on May 29, 2017, 1:33 p.m.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.