View Diabetes IDA (public)

2010-11-24 19:54 by sonne | Version 4 | Rating Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star
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Summary

The diabetes data set from the IDA Benchmark repository.

License
PDDL
Dependencies
Tags
IDA_Benchmark_Repository
Attribute Types
Download
# Instances: 768 / # Attributes: 9
HDF5 (64.5 KB) XML CSV ARFF LibSVM Matlab Octave

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Completeness of this item currently: 77%.
Original Data Format
h5
Name
diabetis_data
Version mldata
0
Comment

matlab

Names
Data (first 10 data points)
    -1.0 -1.14... -1.99... -0.47... -1.28... -0.69... -1.30... 0.79... 2.87...
    -1.0 -1.14... -1.68... 0.35... -1.28... -0.69... 1.68... -0.83... 1.08...
    -1.0 -1.14... -1.49... -3.57... -1.28... -0.69... -1.38... -0.39... -0.70...
    -1.0 -1.14... -1.46... -0.88... -0.66... -0.38... -0.53... -0.61... -0.95...
    -1.0 -1.14... -1.34... 0.97... 0.53... -0.34... 0.62... -0.11... -1.04...
    -1.0 -1.14... -1.15... -0.26... 0.09... -0.11... 0.48... 0.22... -1.04...
    -1.0 -1.14... -1.15... 0.66... 0.65... 0.39... 0.78... -0.72... -0.87...
    -1.0 -1.14... -1.09... -0.05... 0.71... -0.69... 0.48... -0.70... -0.70...
    -1.0 -1.14... -0.93... -0.05... 0.71... 1.12... 1.00... -0.27... -0.70...
    -1.0 -1.14... -0.93... 0.56... -1.28... -0.69... 0.05... 0.38... -0.53...
    ... ... ... ... ... ... ... ... ...
Description

data set information

number of train patterns : 468 number of test patterns : 300 input dimension : 8 output dimension : 1 number of realizations of the data: 100

URLs
http://www.ics.uci.edu/~mlearn/MLSummary.html
Publications
    Data Source
    Measurement Details

    modifications of the original data

    training data has now zero mean and standard deviation one

    Usage Scenario
    revision 1
    by sonne on 2010-04-28 12:53
    revision 2
    by sonne on 2010-11-24 19:40
    revision 3
    by sonne on 2010-11-24 19:42
    revision 4
    by sonne on 2010-11-24 19:54

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    Acknowledgements

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