# Sample of UCI Machine Learning Forest Cover Dataset

### Description

Dataset used as test data in the study cited below. These are observations 11341 to 15120, 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.

### Usage

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### Format

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

### Details

For further 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.

### Source

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

### References

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.

### Examples

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