View statlib-20050214 balloon (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: 2001 / # Attributes: 3
HDF5 (50.8 KB) XML CSV ARFF LibSVM Matlab Octave

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Original Data Format
arff
Name
balloon
Version mldata
0
Comment

The data consist of 2001 observations taken from a balloon about 30 kilometres above the surface of the earth. In the section of the flight shown here the balloon increases in height. As radiation increases with height there is a non-decreasing trend in the data. The outliers are caused by the fact that the balloon slowly rotates, causing the ropes from which the measuring instrument is suspended to cut off the direct radiation from the sun. The first column contains the raw data, the second column the residuals after the removal of a non-decreasing trend. Reference: Davies, L. and Gather, U. (1993), "The Identification of Multiple Outliers" (discussion paper), to appear in JASA. Mailing address: Laurie Davies Universitaet-Gesamthochschule Essen Fachbereich 6 Mathematik Universitaetsstrasse 3 D-4300 Essen 1 Germany

Information about the dataset CLASSTYPE: numeric CLASSINDEX: last

Names
id,raw,residual,
Types
  1. numeric
  2. numeric
  3. numeric
Data (first 10 data points)
    id raw resi...
    1.0 1.76 0.0
    2.0 1.76 0.0
    3.0 1.76 0.0
    4.0 1.76 0.0
    5.0 1.74 -0.02
    6.0 1.72 -0.04
    7.0 1.68 -0.082
    8.0 1.68 -0.091
    9.0 1.76 -0.019
    10.0 1.84 0.055
    ... ... ...
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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