View datasets-numeric mbagrade (public)

2010-11-06 09:57 by mldata | Version 1 | Rating Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star
Rating
Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star Overall (based on 0 votes)
Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star Interesting
Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star Documentation
Summary

(No information yet)

License
unknown (from Weka repository)
Dependencies
Tags
arff slurped Weka
Attribute Types
Integer,Floating Point
Download
# Instances: 61 / # Attributes: 3
HDF5 (10.8 KB) XML CSV ARFF LibSVM Matlab Octave
Completeness of this item currently: 44%.
You can edit this item to add more meta information and make use of the site's premium features.
Original Data Format
arff
Name
mbagrade
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.

Names
sex,GMAT,grade_point_average,
Types
  1. nominal:0,1
  2. numeric
  3. numeric
Data (first 10 data points)
    sex GMAT grad...
    0.0 590.0 3.252
    0.0 550.0 3.329
    1.0 680.0 3.319
    0.0 520.0 3.133
    0.0 560.0 2.986
    0.0 540.0 3.505
    1.0 500.0 2.648
    1.0 600.0 3.09
    0.0 440.0 3.205
    0.0 680.0 3.876
    ... ... ...
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 4685 times and viewed 2586 times.

    No Tasks yet on dataset datasets-numeric mbagrade

    Submit a new Task for this Data item

    Data

    Sort by

    Disclaimer

    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.

    Data | Task | Method | Challenge

    Acknowledgements

    This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
    PASCAL Logo
    http://www.pascal-network.org/.