autoMpg
From MaRDI portal
Dataset:6032997
OpenML dataset with id 196
No author found.
Full work available at URL: https://api.openml.org/data/v1/download/3633/autoMpg.arff
Upload date: 23 April 2014
Dataset Characteristics
Number of classes: 0
Number of features: 8 (numeric: 5, symbolic: 3 and in total binary: 0 )
Number of instances: 398
Number of instances with missing values: 6
Number of missing values: 6
Author: Source: Unknown - Please cite:
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Identifier attribute deleted.
As used by Kilpatrick, D. & Cameron-Jones, M. (1998). Numeric prediction using instance-based learning with encoding length selection. In Progress in Connectionist-Based Information Systems. Singapore: Springer-Verlag.
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
1. Title: Auto-Mpg Data
2. Sources:
(a) Origin: This dataset was taken from the StatLib library which is
maintained at Carnegie Mellon University. The dataset was
used in the 1983 American Statistical Association Exposition.
(c) Date: July 7, 1993
3. Past Usage:
- See 2b (above)
- Quinlan,R. (1993). Combining Instance-Based and Model-Based Learning.
In Proceedings on the Tenth International Conference of Machine
Learning, 236-243, University of Massachusetts, Amherst. Morgan
Kaufmann.
4. Relevant Information:
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", 8 of the original instances were removed
because they had unknown values for the "mpg" attribute. The original
dataset is available in the file "auto-mpg.data-original".
"The data concerns city-cycle fuel consumption in miles per gallon,
to be predicted in terms of 3 multivalued discrete and 5 continuous
attributes." (Quinlan, 1993)
5. Number of Instances: 398
6. Number of Attributes: 9 including the class attribute
7. Attribute Information:
1. mpg: continuous
2. cylinders: multi-valued discrete
3. displacement: continuous
4. horsepower: continuous
5. weight: continuous
6. acceleration: continuous
7. model year: multi-valued discrete
8. origin: multi-valued discrete
9. car name: string (unique for each instance)
8. Missing Attribute Values: horsepower has 6 missing values
This page was built for dataset: autoMpg