View datasets-numeric baskball (public)
























- Summary
(No information yet)
- License
- unknown (from Weka repository)
- Dependencies
- Tags
- arff slurped Weka
- Attribute Types
- Integer,Floating Point
- Download
-
# Instances: 96 / # Attributes: 5
HDF5 (13.6 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
- baskball
- 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.
Points scored per minute is being treated as the class attribute.
- Names
- assists_per_minute,height,time_played,age,points_per_minute,
- Types
- numeric
- numeric
- numeric
- numeric
- numeric
- Data (first 10 data points)
assi... height time... age poin... 0.0888 201.0 36.02 28.0 0.5885 0.1399 198.0 39.32 30.0 0.8291 0.0747 198.0 38.8 26.0 0.4974 0.0983 191.0 40.71 30.0 0.5772 0.1276 196.0 38.4 28.0 0.5703 0.1671 201.0 34.1 31.0 0.5835 0.1906 193.0 36.2 30.0 0.5276 0.1061 191.0 36.75 27.0 0.5523 0.2446 185.0 38.43 29.0 0.4007 0.167 203.0 33.54 24.0 0.477 ... ... ... ... ...
- 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 2011-09-14 16:26
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 8402 times and viewed 4166 times.
No Tasks yet on dataset datasets-numeric baskball
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/.