vowel.arff

一个简单灵活的数据挖掘实验平台

% 
%                 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
% [e-mail]
% 
% 
% 
%                 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