View German IDA (public)

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Summary

The German data set from the IDA Benchmark repository.

License
PDDL
Dependencies
Tags
IDA_Benchmark_Repository
Attribute Types
Download
# Instances: 1000 / # Attributes: 20
HDF5 (174.6 KB) XML CSV ARFF LibSVM Matlab Octave

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Completeness of this item currently: 66%.
Original Data Format
h5
Name
german_data
Version mldata
0
Comment

matlab

Names
Data (first 10 data points)
    1.0 -1.25... -1.23... -1.42... -0.02... -0.73... -0.69... 1.33... 0.91... -0.96... ...
    -1.0 -1.25... -1.23... -0.50... -0.17... -0.92... -0.69... -1.14... 0.02... 0.44... ...
    -1.0 -1.25... -1.23... -0.50... -0.17... -0.73... -0.06... 1.33... 0.02... 0.44... ...
    -1.0 -1.25... -1.23... -0.50... -0.17... -0.67... 1.83... -1.97... 0.91... -0.96... ...
    1.0 -1.25... -1.23... -0.50... -0.17... 4.11... -0.69... 1.33... -1.76... 0.44... ...
    -1.0 -1.25... -1.23... -0.50... -0.15... -0.67... 0.56... -1.97... -1.76... -0.96... ...
    -1.0 -1.25... -1.23... -0.50... -0.12... -1.00... -0.69... 1.33... -0.86... -0.96... ...
    -1.0 -1.25... -1.23... -0.50... -0.12... -0.67... -0.69... -0.31... -1.76... 0.44... ...
    -1.0 -1.25... -1.23... -0.50... -0.10... -0.22... 0.56... -0.31... -0.86... 0.44... ...
    -1.0 -1.25... -1.23... -0.50... -0.07... -1.03... -0.69... -1.14... 0.91... -0.96... ...
    ... ... ... ... ... ... ... ... ... ... ...
Description

(No information yet)

URLs
http://www.ics.uci.edu/~mlearn/MLSummary.html
Publications
  • @techreport{RaeOnoMue98b, author = {G.~R{"a}tsch and T.~Onoda and K.-R.~M{"u}ller}, title = "Soft Margins for {A}da{B}oost", institution = {Department of Computer Science, Royal Holloway, University of London}, month = aug, year = {1998}, address = {Egham, UK}, number = {NC-TR-1998-021}, note = "Submitted to Machine Learning.", url = "http://www.first.gmd.de/~raetsch/Neurocolt_Margin.ps.gz", }

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 15:56
revision 2
by sonne on 2011-09-14 15:17

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Acknowledgements

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