covtest: Sample of UCI Machine Learning Forest Cover Dataset
In DAAGxtras: Data Sets and Functions, supplementary to DAAG
Description
Usage
Format
Details
Source
References
Examples
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
1
Format
A data frame with 11318 observations on the following 55 variables.
V1a numeric vector
V2a numeric vector
V3a numeric vector
V4a numeric vector
V5a numeric vector
V6a numeric vector
V7a numeric vector
V8a numeric vector
V9a numeric vector
V10a numeric vector
V11a numeric vector
V12a numeric vector
V13a numeric vector
V14a numeric vector
V15a numeric vector
V16a numeric vector
V17a numeric vector
V18a numeric vector
V19a numeric vector
V20a numeric vector
V21a numeric vector
V22a numeric vector
V23a numeric vector
V24a numeric vector
V25a numeric vector
V26a numeric vector
V27a numeric vector
V28a numeric vector
V29a numeric vector
V30a numeric vector
V31a numeric vector
V32a numeric vector
V33a numeric vector
V34a numeric vector
V35a numeric vector
V36a numeric vector
V37a numeric vector
V38a numeric vector
V39a numeric vector
V40a numeric vector
V41a numeric vector
V42a numeric vector
V43a numeric vector
V44a numeric vector
V45a numeric vector
V46a numeric vector
V47a numeric vector
V48a numeric vector
V49a numeric vector
V50a numeric vector
V51a numeric vector
V52a numeric vector
V53a numeric vector
V54a numeric vector
V55a 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
1
Example output
DAAGxtras documentation built on May 1, 2019, 10:18 p.m.
R Package Documentation
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Description Usage Format Details Source References Examples
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
1 |
Format
A data frame with 11318 observations on the following 55 variables.
V1a numeric vector
V2a numeric vector
V3a numeric vector
V4a numeric vector
V5a numeric vector
V6a numeric vector
V7a numeric vector
V8a numeric vector
V9a numeric vector
V10a numeric vector
V11a numeric vector
V12a numeric vector
V13a numeric vector
V14a numeric vector
V15a numeric vector
V16a numeric vector
V17a numeric vector
V18a numeric vector
V19a numeric vector
V20a numeric vector
V21a numeric vector
V22a numeric vector
V23a numeric vector
V24a numeric vector
V25a numeric vector
V26a numeric vector
V27a numeric vector
V28a numeric vector
V29a numeric vector
V30a numeric vector
V31a numeric vector
V32a numeric vector
V33a numeric vector
V34a numeric vector
V35a numeric vector
V36a numeric vector
V37a numeric vector
V38a numeric vector
V39a numeric vector
V40a numeric vector
V41a numeric vector
V42a numeric vector
V43a numeric vector
V44a numeric vector
V45a numeric vector
V46a numeric vector
V47a numeric vector
V48a numeric vector
V49a numeric vector
V50a numeric vector
V51a numeric vector
V52a numeric vector
V53a numeric vector
V54a numeric vector
V55a 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
1 |
Example output
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