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autoMpg

autoMpg

active ARFF Public Domain (CC0) Visibility: public Uploaded 19-04-2020 by Rafael Gomes Mantovani
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Auto MPG (6 variables) dataset The data concerns city-cycle fuel consumption in miles per gallon (Mpg), to be predicted in terms of 1 multivalued discrete and 5 continuous attributes (two multivalued discrete attributes (Cylinders and Origin) from the original dataset (autoMPG6) are removed). This dataset is a slightly modified version of the dataset provided in the StatLib library. In line with the use by Ross Quinlan (1993) in predicting the attribute Mpg, 6 of the original instances were removed because they had unknown values for the Mpg attribute.

6 features

Mpg (target)numeric127 unique values
0 missing
Displacementnumeric81 unique values
0 missing
Horse_powernumeric93 unique values
0 missing
Weightnumeric346 unique values
0 missing
Accelerationnumeric95 unique values
0 missing
Model_yearnumeric13 unique values
0 missing

19 properties

392
Number of instances (rows) of the dataset.
6
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.
6
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of instances having missing values.
-7.67
Average class difference between consecutive instances.
0
Percentage of missing values.
0.02
Number of attributes divided by the number of instances.
100
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.

8 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: Mpg
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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