OpenML
visualizing_soil

visualizing_soil

active ARFF Publicly available Visibility: public Uploaded 18-06-2022 by Leo Grin
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  • Computer Systems Machine Learning
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Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "regression on categorical and numerical features" benchmark. Original description: Author: Source: Unknown - Date unknown Please cite: This S dump contains 22 data sets from the book Visualizing Data published by Hobart Press (books@hobart.com). The dump was created by data.dump() and can be read back into S by data.restore(). The name of each S data set is the name of the data set used in the book. To find the description of the data set in the book look under the entry - data, name - in the index. For example, one data set is barley. To find the description of barley, look in the index under the entry - data, barley. File: ../data/visualizing/soil.csv Information about the dataset CLASSTYPE: numeric CLASSINDEX: none specific

5 features

track (target)numeric40 unique values
0 missing
northingnumeric7011 unique values
0 missing
eastingnumeric6069 unique values
0 missing
resistivitynumeric5726 unique values
0 missing
isnsnominal2 unique values
0 missing

19 properties

8641
Number of instances (rows) of the dataset.
5
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
4
Number of numeric attributes.
1
Number of nominal attributes.
Number of instances belonging to the least frequent class.
1
Number of binary attributes.
20
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.99
Average class difference between consecutive instances.
0
Percentage of missing values.
0
Number of attributes divided by the number of instances.
80
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
20
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.

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