Context The data is technical spec of cars. The dataset is downloaded from https://www.kaggle.com/datasets/uciml/autompg-dataset
Content Title: Auto-Mpg Data
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
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. 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)
Number of Instances: 398
Number of Attributes: 9 including the class attribute
Attribute Information:
mpg: continuous cylinders: multi-valued discrete displacement: continuous horsepower: continuous weight: continuous acceleration: continuous model year: multi-valued discrete origin: multi-valued discrete car name: string (unique for each instance) Missing Attribute Values: horsepower has 6 missing values
Acknowledgements Dataset: UCI Machine Learning Repository Data link : https://archive.ics.uci.edu/ml/datasets/auto+mpg
Inspiration:
I have used this dataset for practicing my exploratory analysis skills.