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2010-11-06 09:58 by mldata | Version 1 | Rating

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Summary: (No information yet)
License: unknown (from Weka repository)
Dependencies
Tags: arff slurped Weka
Attribute Types: Floating Point,String
Download: # Instances: 990 / # Attributes: 14
HDF5 (248.8 KB) XML CSV ARFF LibSVM Matlab Octave
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Original Data Format

arff

Name

vowel

Version mldata

Comment

            Introduction
            ============

In my work on context-sensitive learning, I used the "Deterding Vowel Recognition Data", but I found it necessary to reformulate the data. Implicit in the original data is contextual information on the speaker's gender and identity. For my work, it was necessary to make this information explicit. The file "vowel-context.data" adds the speaker's sex and identity as new features. The format of the data file is described below.

Peter Turney peter@ai.iit.nrc.ca

            References
            ==========

P. Turney. "Robust Classification With Context-Sensitive Features." Proceedings of the Sixth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE-93): 268-276. 1993.

URL: ftp://ai.iit.nrc.ca/pub/ksl-papers/NRC-35074.ps.Z

P. Turney. "Exploiting Context When Learning to Classify." Proceedings of the European Conference on Machine Learning (ECML-93): 402-407. 1993.

URL: ftp://ai.iit.nrc.ca/pub/ksl-papers/NRC-35058.ps.Z

            File Structure
            ==============

    Column          Description
    -------------------------------
    0               Train or Test
    1               Speaker Number
    2               Sex
    3               Feature 0
    4               Feature 1
    5               Feature 2
    6               Feature 3
    7               Feature 4
    8               Feature 5
    9               Feature 6
    10              Feature 7
    11              Feature 8
    12              Feature 9
    13              Class



            Numerical Codes
            ===============

    Speaker         Code Number
    ---------------------------
    Andrew          0
    Bill            1
    David           2
    Mark            3
    Jo              4
    Kate            5
    Penny           6
    Rose            7
    Mike            8
    Nick            9
    Rich            10
    Tim             11
    Sarah           12
    Sue             13
    Wendy           14



    Set             Number
    ---------------------------
    Train           0
    Test            1



    Sex             Number
    ---------------------------
    Male            0
    Female          1



    Class           Number
    ---------------------------
    hid             0
    hId             1
    hEd             2
    hAd             3
    hYd             4
    had             5
    hOd             6
    hod             7
    hUd             8
    hud             9
    hed             10





    Speaker         Code Number     Sex             Train/Test
    ---------------------------------------------------------------
    Andrew          0               0               0
    Bill            1               0               0
    David           2               0               0
    Mark            3               0               0
    Jo              4               1               0
    Kate            5               1               0
    Penny           6               1               0
    Rose            7               1               0
    Mike            8               0               1
    Nick            9               0               1
    Rich            10              0               1
    Tim             11              0               1
    Sarah           12              1               1
    Sue             13              1               1
    Wendy           14              1               1

Num Instances: 990 Num Attributes: 14 Num missing: 0 / 0.0%

name                      type enum ints real     missing    distinct  (1)

1 'Train or Test' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 2 'Speaker Number' Enum 0% 100% 0% 0 / 0% 15 / 2% 0% 3 'Sex' Enum 0% 100% 0% 0 / 0% 2 / 0% 0% 4 'Feature 0' Real 0% 0% 100% 0 / 0% 853 / 86% 74% 5 'Feature 1' Real 0% 0% 100% 0 / 0% 877 / 89% 78% 6 'Feature 2' Real 0% 0% 100% 0 / 0% 815 / 82% 67% 7 'Feature 3' Real 0% 0% 100% 0 / 0% 836 / 84% 71% 8 'Feature 4' Real 0% 0% 100% 0 / 0% 803 / 81% 66% 9 'Feature 5' Real 0% 0% 100% 0 / 0% 798 / 81% 64% 10 'Feature 6' Real 0% 0% 100% 0 / 0% 748 / 76% 57% 11 'Feature 7' Real 0% 0% 100% 0 / 0% 794 / 80% 64% 12 'Feature 8' Real 0% 0% 100% 0 / 0% 788 / 80% 63% 13 'Feature 9' Real 0% 0% 100% 0 / 0% 775 / 78% 60% 14 'Class' Enum 0% 100% 0% 0 / 0% 11 / 1% 0%

Relabeled values in attribute 'Speaker Number' From: 0 To: Andrew
From: 1 To: Bill
From: 2 To: David
From: 3 To: Mark
From: 4 To: Jo
From: 5 To: Kate
From: 6 To: Penny
From: 7 To: Rose
From: 8 To: Mike
From: 9 To: Nick
From: 10 To: Rich
From: 11 To: Tim
From: 12 To: Sarah
From: 13 To: Sue
From: 14 To: Wendy

Relabeled values in attribute 'Sex' From: 0 To: Male
From: 1 To: Female

Relabeled values in attribute 'Class' From: 0 To: hid
From: 1 To: hId
From: 2 To: hEd
From: 3 To: hAd
From: 4 To: hYd
From: 5 To: had
From: 6 To: hOd
From: 7 To: hod
From: 8 To: hUd
From: 9 To: hud
From: 10 To: hed

Names

Train or Test,Speaker Number,Sex,Feature 0,Feature 1,Feature 2,Feature 3,Feature 4,Feature 5,Feature 6,

Types

nominal:Train,Test
nominal:Andrew,Bill,David,Mark,Jo,Kate,Penny,Rose,Mike,Nick,Rich,Tim,Sarah,Sue,Wendy
nominal:Male,Female
numeric
numeric
numeric
numeric
numeric
numeric
numeric

Data (first 10 data points)

Trai...	Spea...	Sex	Feat...	Feat...	Feat...	Feat...	Feat...	Feat...	Feat...	...
Train	Andrew	Male	-3.639	0.418	-0.67	1.779	-0.168	1.627	-0.388	...
Train	Andrew	Male	-3.327	0.496	-0.694	1.365	-0.265	1.933	-0.363	...
Train	Andrew	Male	-2.12	0.894	-1.576	0.147	-0.707	1.559	-0.579	...
Train	Andrew	Male	-2.287	1.809	-1.498	1.012	-1.053	1.06	-0.567	...
Train	Andrew	Male	-2.598	1.938	-0.846	1.062	-1.633	0.764	0.394	...
Train	Andrew	Male	-2.852	1.914	-0.755	0.825	-1.588	0.855	0.217	...
Train	Andrew	Male	-3.482	2.524	-0.433	1.048	-1.995	0.902	0.322	...
Train	Andrew	Male	-3.941	2.305	0.124	1.771	-1.815	0.593	-0.435	...
Train	Andrew	Male	-3.86	2.116	-0.939	0.688	-0.675	1.679	-0.512	...
Train	Andrew	Male	-3.648	1.812	-1.378	1.578	0.065	1.577	-0.466	...
...	...	...	...	...	...	...	...	...	...	...

Description

A gzip'ed tar containing UCI and UCI KDD datasets (uci-20070111.tar.gz, 17,952,832 Bytes)

URLs

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Data Source

http://www.ics.uci.edu/~mlearn/MLRepository.html http://kdd.ics.uci.edu/

Measurement Details

Usage Scenario

revision 1: by mldata on 2010-11-06 09:58

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Acknowledgements

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

http://www.pascal-network.org/.