View statlib-20050214 hip (public)

2010-11-06 10:00 by mldata | Version 1 | Rating Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star
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Summary

(No information yet)

License
unknown (from Weka repository)
Dependencies
Tags
arff slurped Weka
Attribute Types
Integer,Floating Point
Download
# Instances: 54 / # Attributes: 8
HDF5 (12.9 KB) XML CSV ARFF LibSVM Matlab Octave
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Original Data Format
arff
Name
hip
Version mldata
0
Comment

This is the hip measurement data from Table B.13 in Chatfield's Problem Solving (1995, 2nd edn, Chapman and Hall). It is given in 8 columns. First 4 columns are for Control Group. Last 4 columns are for Treatment group (Note there is no pairing. Patient 1 in Control Group is NOT patient 1 in Treatment Group).

Information about the dataset CLASSTYPE: numeric CLASSINDEX: none specific

Names
control_1,control_2,control_3,control_4,treatment_1,treatment_2,treatment_3,treatment_4,
Types
  1. numeric
  2. numeric
  3. numeric
  4. numeric
  5. numeric
  6. numeric
  7. numeric
  8. numeric
Data (first 10 data points)
    cont... cont... cont... cont... trea... trea... trea... trea...
    100.0 100.0 23.0 17.0 125.0 126.0 25.0 36.0
    105.0 103.0 18.0 12.0 120.0 127.0 35.0 37.0
    114.0 115.0 21.0 24.0 135.0 135.0 28.0 40.0
    115.0 116.0 28.0 27.0 135.0 135.0 24.0 34.0
    123.0 126.0 25.0 29.0 100.0 113.0 26.0 30.0
    126.0 121.0 26.0 27.0 110.0 115.0 24.0 26.0
    105.0 110.0 35.0 33.0 122.0 123.0 22.0 42.0
    105.0 102.0 33.0 24.0 122.0 125.0 24.0 37.0
    120.0 123.0 25.0 30.0 124.0 126.0 29.0 29.0
    123.0 118.0 22.0 27.0 124.0 135.0 28.0 31.0
    ... ... ... ... ... ... ... ...
Description

A gzip'ed tar containing StatLib datasets (statlib-20050214.tar.gz, 12,785,582 Bytes)

URLs
(No information yet)
Publications
    Data Source
    http://lib.stat.cmu.edu/datasets/
    Measurement Details
    Usage Scenario
    revision 1
    by mldata on 2010-11-06 10:00

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    Acknowledgements

    This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
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