View datasets-numeric gascons (public)
























- Summary
(No information yet)
- License
- unknown (from Weka repository)
- Dependencies
- Tags
- arff slurped Weka
- Attribute Types
- Integer,Floating Point
- Download
-
# Instances: 27 / # Attributes: 5
HDF5 (11.4 KB) XML CSV ARFF LibSVM Matlab Octave
You can edit this item to add more meta information and make use of the site's premium features.
- Original Data Format
- arff
- Name
- gascons
- Version mldata
- 0
- Comment
Dataset from Smoothing Methods in Statistics (ftp stat.cmu.edu/datasets)
Simonoff, J.S. (1996). Smoothing Methods in Statistics. New York: Springer-Verlag.
Gasoline comnsumption is being treated as the class attribute.
- Names
- year,price_index_for_casoline,disposable_income,price_index_for_used_cars,gasoline_consumption,
- Types
- numeric
- numeric
- numeric
- numeric
- numeric
- Data (first 10 data points)
year pric... disp... pric... gaso... 1960.0 0.925 6036.0 0.836 129.7 1961.0 0.914 6113.0 0.869 131.3 1962.0 0.919 6271.0 0.948 137.1 1963.0 0.918 6378.0 0.96 141.6 1964.0 0.914 6727.0 1.001 148.8 1965.0 0.949 7027.0 0.994 155.9 1966.0 0.97 7280.0 0.97 164.9 1967.0 1.0 7513.0 1.0 171.0 1968.0 1.014 7728.0 1.028 183.4 1969.0 1.047 7891.0 1.031 195.8 ... ... ... ... ...
- Description
A jarfile containing 37 regression problems, obtained from various sources (datasets-numeric.jar, 169,344 Bytes).
- URLs
- (No information yet)
- Publications
- Data Source
- Measurement Details
- Usage Scenario
- revision 1
- by mldata on 2010-11-06 09:57
No one has posted any comments yet. Perhaps you would like to be the first?
Leave a comment
To post a comment, please sign in.This item was downloaded 4533 times and viewed 2210 times.
No Tasks yet on dataset datasets-numeric gascons
Submit a new Task for this Data itemDisclaimer
We are acting in good faith to make datasets submitted for the use of the scientific community available to everybody, but if you are a copyright holder and would like us to remove a dataset please inform us and we will do it as soon as possible.
Acknowledgements
This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
http://www.pascal-network.org/.