contact-lenses.arff

一个matlab的工具包,里面包括一些分类器 例如 KNN KMEAN SVM NETLAB 等等有很多.

% 1. Title: Database for fitting contact lenses
% 
% 2. Sources:
%      (a) Cendrowska, J. "PRISM: An algorithm for inducing modular rules",
%          International Journal of Man-Machine Studies, 1987, 27, 349-370
%      (b) Donor: Benoit Julien ([e-mail])
%      (c) Date: 1 August 1990
% 
% 3. Past Usage:
%       1. See above.
%       2. Witten, I. H. & MacDonald, B. A. (1988). Using concept
%          learning for knowledge acquisition. International Journal of
%          Man-Machine Studies, 27, (pp. 349-370).
% 
%  Notes:  This database is complete (all possible combinations of
%          attribute-value pairs are represented).
% 
%          Each instance is complete and correct.
% 
%          9 rules cover the training set.
% 
% 4. Relevant Information Paragraph:
%     The examples are complete and noise free.
%     The examples highly simplified the problem. The attributes do not
%     fully describe all the factors affecting the decision as to which type,
%     if any, to fit.
% 
% 5. Number of Instances: 24
% 
% 6. Number of Attributes: 4 (all nominal)
% 
% 7. Attribute Information:
%     -- 3 Classes
%      1 : the patient should be fitted with hard contact lenses,
%      2 : the patient should be fitted with soft contact lenses,
%      1 : the patient should not be fitted with contact lenses.
% 
%     1. age of the patient: (1) young, (2) pre-presbyopic, (3) presbyopic
%     2. spectacle prescription:  (1) myope, (2) hypermetrope
%     3. astigmatic:     (1) no, (2) yes
%     4. tear production rate:  (1) reduced, (2) normal
% 
% 8. Number of Missing Attribute Values:   0
% 
% 9. Class Distribution:
%    1. hard contact lenses: 4
%    2. soft contact lenses: 5
%    3. no contact lenses: 15

@relation contact-lenses

@attribute age 			{young, pre-presbyopic, presbyopic}
@attribute spectacle-prescrip	{myope, hypermetrope}
@attribute astigmatism		{no, yes}
@attribute tear-prod-rate	{reduced, normal}
@attribute contact-lenses	{soft, hard, none}

@data
%
% 24 instances
%
young,myope,no,reduced,none
young,myope,no,normal,soft
young,myope,yes,reduced,none
young,myope,yes,normal,hard
young,hypermetrope,no,reduced,none
young,hypermetrope,no,normal,soft
young,hypermetrope,yes,reduced,none
young,hypermetrope,yes,normal,hard
pre-presbyopic,myope,no,reduced,none
pre-presbyopic,myope,no,normal,soft
pre-presbyopic,myope,yes,reduced,none
pre-presbyopic,myope,yes,normal,hard
pre-presbyopic,hypermetrope,no,reduced,none
pre-presbyopic,hypermetrope,no,normal,soft
pre-presbyopic,hypermetrope,yes,reduced,none
pre-presbyopic,hypermetrope,yes,normal,none
presbyopic,myope,no,reduced,none
presbyopic,myope,no,normal,none
presbyopic,myope,yes,reduced,none
presbyopic,myope,yes,normal,hard
presbyopic,hypermetrope,no,reduced,none
presbyopic,hypermetrope,no,normal,soft
presbyopic,hypermetrope,yes,reduced,none
presbyopic,hypermetrope,yes,normal,none