prnn_crabs.arff

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StatLib/nominal/prnn_crabs.arff
StatLib
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2009-11-10 12:52:52
Description

Data from Campbell & Mahon (1974) on the morphology of rock crabs of genus Leptograpsus.
File contents

% Datasets for `Pattern Recognition and Neural Networks' by B.D. Ripley
% =====================================================================
% 
% Cambridge University Press (1996)  ISBN  0-521-46086-7
% 
% The background to the datasets is described in section 1.4; this file
% relates the computer-readable files to that description.
% 
% 
% 
% Cushing's syndrome
% ------------------
% 
% Data from Aitchison & Dunsmore (1975, Tables 11.1-3).
% 
% Data file Cushings.dat has four columns, 
% 
% Label of the patient
% Tetrhydrocortisone  (mg/24hr)
% Pregnanetriol  (mg/24hr)
% Type
% 
% The type of the last six patients (u1 to u6) should be
% regarded as unknown.  (The code `o' indicates `other').
% 
% 
% 
% synthetic two-class problem
% ---------------------------
% 
% Data from Ripley (1994a).
% 
% This has two real-valued co-ordinates (xs and ys) and a class (xc)
% which is 0 or 1.
% 
% Data file  synth.tr   has 250 rows of the training set
%            synth.te   has 1000 rows of the test set  (not used here)
% 
% 
% 
% viruses
% -------
% 
% This is a dataset on 61 viruses with rod-shaped particles affecting
% various crops (tobacco, tomato, cucumber and others) described by
% {Fauquet et al. (1988) and analysed by Eslava-G\'omez (1989).  There
% are 18 measurements on each virus,  the number of amino acid residues
% per molecule of coat protein.
% 
% Data file  viruses.dat  has 61 rows of 18 counts
% 	   virus3.dat   has 38 rows corresponding to the distinct
% 	   		Tobamoviruses.
% 
% The whole dataset is in order Hordeviruses (3), Tobraviruses (6),
% Tobamoviruses (39) and `furoviruses' (13).
% 
% 
% 
% Leptograpsus crabs
% ------------------
% 
% Data from Campbell & Mahon (1974) on the morphology of rock crabs of
% genus Leptograpsus.
% 
% There are 50 specimens of each sex of each of two colour forms.
% 
% Data file  crabs.dat has rows
% 
% sp	`species', coded B (blue form) or O (orange form)
% sex	coded M or F
% index	within each group of 50
% FL	frontal lip of carapace (mm)
% RW	rear width of carapace (mm)
% CL	length along the midline of carapace (mm)
% CW	maximum width of carapace (mm)
% BD	body depth (mm)
% 
% 
% 
% Forensic glass
% --------------
% 
% This example comes from forensic testing of glass collected by
% B. German on 214 fragments of glass.  It is also contained in the
% UCI machine-learning database collection (Murphy & Aha, 1995).
% 
% Data file fglass.dat has 214 rows with data for a single glass
% fragment.
% 
% RI	refractive index
% Na	% weight of sodium oxide(s)
% Mg	% weight of magnesium oxide(s)
% Al	% weight of aluminium oxide(s)
% Si	% weight of silicon oxide(s)
% K	% weight of potassium oxide(s)
% Ca	% weight of calcium oxide(s)
% Ba	% weight of barium oxide(s)
% Fe	% weight of iron oxide(s)
% type	coded 1 to 7
% 
% The type codes are:
% 
% 	1 (WinF) window float glass
% 	2 (WinNF) window non-float glass
% 	3 (Veh) vehicle glass
% 	5 (Con)  containers
% 	6 (Tabl) tableware
% 	7 (Head) vehicle headlamp glass
% 
% The ten groups used for the cross-validation experiments (I believe)
% are listed as row numbers in the file fglass.grp,
% 
% 
% 
% Diabetes in Pima Indians
% ------------------------
% 
% A population of women who were at least 21 years old, of Pima Indian heritage
% and living near Phoenix, Arizona,  was tested for diabetes
% according to World Health Organization criteria.  The data
% were collected by the US National Institute of Diabetes and Digestive and
% Kidney Diseases (Smith et al, 1988). This example is also contained in the
% UCI machine-learning database collection (Murphy & Aha, 1995).
% 
% The data files have rows containing
% 
% npreg 	number of pregnancies
% glu 	plasma glucose concentration in an oral glucose tolerance test
% bp 	diastolic blood pressure (mm Hg)
% skin 	triceps skin fold thickness (mm)
% ins	serum insulin (micro U/ml)
% bmi 	body mass index (weight in kg/(height in m)^2)
% ped 	diabetes pedigree function
% age 	in years
% type	No / Yes
% 
% Data file pima.tr   has 200 rows of complete training data.
%           pima.te   has 332 rows of complete test data.
%           pima.tr2  has the 200 rows of pima.tr plus 100 incomplete rows.
% 
%
%
% Information about the dataset
% CLASSTYPE: nominal
% CLASSINDEX: 1
%

@relation prnn-crabs

@attribute sp {blue_form,orange_form}
@attribute sex {Female,Male}
@attribute index INTEGER
@attribute FL REAL
@attribute RW REAL
@attribute CL REAL
@attribute CW REAL
@attribute BD REAL

@data
blue_form,Male,1,8.1,6.7,16.1,19.0,7.0
blue_form,Male,2,8.8,7.7,18.1,20.8,7.4
blue_form,Male,3,9.2,7.8,19.0,22.4,7.7
blue_form,Male,4,9.6,7.9,20.1,23.1,8.2
blue_form,Male,5,9.8,8.0,20.3,23.0,8.2
blue_form,Male,6,10.8,9.0,23.0,26.5,9.8
blue_form,Male,7,11.1,9.9,23.8,27.1,9.8
blue_form,Male,8,11.6,9.1,24.5,28.4,10.4
blue_form,Male,9,11.8,9.6,24.2,27.8,9.7
blue_form,Male,10,11.8,10.5,25.2,29.3,10.3
blue_form,Male,11,12.2,10.8,27.3,31.6,10.9
blue_form,Male,12,12.3,11.0,26.8,31.5,11.4
blue_form,Male,13,12.6,10.0,27.7,31.7,11.4
blue_form,Male,14,12.8,10.2,27.2,31.8,10.9
blue_form,Male,15,12.8,10.9,27.4,31.5,11.0
blue_form,Male,16,12.9,11.0,26.8,30.9,11.4
blue_form,Male,17,13.1,10.6,28.2,32.3,11.0
blue_form,Male,18,13.1,10.9,28.3,32.4,11.2
blue_form,Male,19,13.3,11.1,27.8,32.3,11.3
blue_form,Male,20,13.9,11.1,29.2,33.3,12.1
blue_form,Male,21,14.3,11.6,31.3,35.5,12.7
blue_form,Male,22,14.6,11.3,31.9,36.4,13.7
blue_form,Male,23,15.0,10.9,31.4,36.4,13.2
blue_form,Male,24,15.0,11.5,32.4,37.0,13.4
blue_form,Male,25,15.0,11.9,32.5,37.2,13.6
blue_form,Male,26,15.2,12.1,32.3,36.7,13.6
blue_form,Male,27,15.4,11.8,33.0,37.5,13.6
blue_form,Male,28,15.7,12.6,35.8,40.3,14.5
blue_form,Male,29,15.9,12.7,34.0,38.9,14.2
blue_form,Male,30,16.1,11.6,33.8,39.0,14.4
blue_form,Male,31,16.1,12.8,34.9,40.7,15.7
blue_form,Male,32,16.2,13.3,36.0,41.7,15.4
blue_form,Male,33,16.3,12.7,35.6,40.9,14.9
blue_form,Male,34,16.4,13.0,35.7,41.8,15.2
blue_form,Male,35,16.6,13.5,38.1,43.4,14.9
blue_form,Male,36,16.8,12.8,36.2,41.8,14.9
blue_form,Male,37,16.9,13.2,37.3,42.7,15.6
blue_form,Male,38,17.1,12.6,36.4,42.0,15.1
blue_form,Male,39,17.1,12.7,36.7,41.9,15.6
blue_form,Male,40,17.2,13.5,37.6,43.9,16.1
blue_form,Male,41,17.7,13.6,38.7,44.5,16.0
blue_form,Male,42,17.9,14.1,39.7,44.6,16.8
blue_form,Male,43,18.0,13.7,39.2,44.4,16.2
blue_form,Male,44,18.8,15.8,42.1,49.0,17.8
blue_form,Male,45,19.3,13.5,41.6,47.4,17.8
blue_form,Male,46,19.3,13.8,40.9,46.5,16.8
blue_form,Male,47,19.7,15.3,41.9,48.5,17.8
blue_form,Male,48,19.8,14.2,43.2,49.7,18.6
blue_form,Male,49,19.8,14.3,42.4,48.9,18.3
blue_form,Male,50,21.3,15.7,47.1,54.6,20.0
blue_form,Female,1,7.2,6.5,14.7,17.1,6.1
blue_form,Female,2,9.0,8.5,19.3,22.7,7.7
blue_form,Female,3,9.1,8.1,18.5,21.6,7.7
blue_form,Female,4,9.1,8.2,19.2,22.2,7.7
blue_form,Female,5,9.5,8.2,19.6,22.4,7.8
blue_form,Female,6,9.8,8.9,20.4,23.9,8.8
blue_form,Female,7,10.1,9.3,20.9,24.4,8.4
blue_form,Female,8,10.3,9.5,21.3,24.7,8.9
blue_form,Female,9,10.4,9.7,21.7,25.4,8.3
blue_form,Female,10,10.8,9.5,22.5,26.3,9.1
blue_form,Female,11,11.0,9.8,22.5,25.7,8.2
blue_form,Female,12,11.2,10.0,22.8,26.9,9.4
blue_form,Female,13,11.5,11.0,24.7,29.2,10.1
blue_form,Female,14,11.6,11.0,24.6,28.5,10.4
blue_form,Female,15,11.6,11.4,23.7,27.7,10.0
blue_form,Female,16,11.7,10.6,24.9,28.5,10.4
blue_form,Female,17,11.9,11.4,26.0,30.1,10.9
blue_form,Female,18,12.0,10.7,24.6,28.9,10.5
blue_form,Female,19,12.0,11.1,25.4,29.2,11.0
blue_form,Female,20,12.6,12.2,26.1,31.6,11.2
blue_form,Female,21,12.8,11.7,27.1,31.2,11.9
blue_form,Female,22,12.8,12.2,26.7,31.1,11.1
blue_form,Female,23,12.8,12.2,27.9,31.9,11.5
blue_form,Female,24,13.0,11.4,27.3,31.8,11.3
blue_form,Female,25,13.1,11.5,27.6,32.6,11.1
blue_form,Female,26,13.2,12.2,27.9,32.1,11.5
blue_form,Female,27,13.4,11.8,28.4,32.7,11.7
blue_form,Female,28,13.7,12.5,28.6,33.8,11.9
blue_form,Female,29,13.9,13.0,30.0,34.9,13.1
blue_form,Female,30,14.7,12.5,30.1,34.7,12.5
blue_form,Female,31,14.9,13.2,30.1,35.6,12.0
blue_form,Female,32,15.0,13.8,31.7,36.9,14.0
blue_form,Female,33,15.0,14.2,32.8,37.4,14.0
blue_form,Female,34,15.1,13.3,31.8,36.3,13.5
blue_form,Female,35,15.1,13.5,31.9,37.0,13.8
blue_form,Female,36,15.1,13.8,31.7,36.6,13.0
blue_form,Female,37,15.2,14.3,33.9,38.5,14.7
blue_form,Female,38,15.3,14.2,32.6,38.3,13.8
blue_form,Female,39,15.4,13.3,32.4,37.6,13.8
blue_form,Female,40,15.5,13.8,33.4,38.7,14.7
blue_form,Female,41,15.6,13.9,32.8,37.9,13.4
blue_form,Female,42,15.6,14.7,33.9,39.5,14.3
blue_form,Female,43,15.7,13.9,33.6,38.5,14.1
blue_form,Female,44,15.8,15.0,34.5,40.3,15.3
blue_form,Female,45,16.2,15.2,34.5,40.1,13.9
blue_form,Female,46,16.4,14.0,34.2,39.8,15.2
blue_form,Female,47,16.7,16.1,36.6,41.9,15.4
blue_form,Female,48,17.4,16.9,38.2,44.1,16.6
blue_form,Female,49,17.5,16.7,38.6,44.5,17.0
blue_form,Female,50,19.2,16.5,40.9,47.9,18.1
orange_form,Male,1,9.1,6.9,16.7,18.6,7.4
orange_form,Male,2,10.2,8.2,20.2,22.2,9.0
orange_form,Male,3,10.7,8.6,20.7,22.7,9.2
orange_form,Male,4,11.4,9.0,22.7,24.8,10.1
orange_form,Male,5,12.5,9.4,23.2,26.0,10.8
orange_form,Male,6,12.5,9.4,24.2,27.0,11.2
orange_form,Male,7,12.7,10.4,26.0,28.8,12.1
orange_form,Male,8,13.2,11.0,27.1,30.4,12.2
orange_form,Male,9,13.4,10.1,26.6,29.6,12.0
orange_form,Male,10,13.7,11.0,27.5,30.5,12.2
orange_form,Male,11,14.0,11.5,29.2,32.2,13.1
orange_form,Male,12,14.1,10.4,28.9,31.8,13.5
orange_form,Male,13,14.1,10.5,29.1,31.6,13.1
orange_form,Male,14,14.1,10.7,28.7,31.9,13.3
orange_form,Male,15,14.2,10.6,28.7,31.7,12.9
orange_form,Male,16,14.2,10.7,27.8,30.9,12.7
orange_form,Male,17,14.2,11.3,29.2,32.2,13.5
orange_form,Male,18,14.6,11.3,29.9,33.5,12.8
orange_form,Male,19,14.7,11.1,29.0,32.1,13.1
orange_form,Male,20,15.1,11.4,30.2,33.3,14.0
orange_form,Male,21,15.1,11.5,30.9,34.0,13.9
orange_form,Male,22,15.4,11.1,30.2,33.6,13.5
orange_form,Male,23,15.7,12.2,31.7,34.2,14.2
orange_form,Male,24,16.2,11.8,32.3,35.3,14.7
orange_form,Male,25,16.3,11.6,31.6,34.2,14.5
orange_form,Male,26,17.1,12.6,35.0,38.9,15.7
orange_form,Male,27,17.4,12.8,36.1,39.5,16.2
orange_form,Male,28,17.5,12.0,34.4,37.3,15.3
orange_form,Male,29,17.5,12.7,34.6,38.4,16.1
orange_form,Male,30,17.8,12.5,36.0,39.8,16.7
orange_form,Male,31,17.9,12.9,36.9,40.9,16.5
orange_form,Male,32,18.0,13.4,36.7,41.3,17.1
orange_form,Male,33,18.2,13.7,38.8,42.7,17.2
orange_form,Male,34,18.4,13.4,37.9,42.2,17.7
orange_form,Male,35,18.6,13.4,37.8,41.9,17.3
orange_form,Male,36,18.6,13.5,36.9,40.2,17.0
orange_form,Male,37,18.8,13.4,37.2,41.1,17.5
orange_form,Male,38,18.8,13.8,39.2,43.3,17.9
orange_form,Male,39,19.4,14.1,39.1,43.2,17.8
orange_form,Male,40,19.4,14.4,39.8,44.3,17.9
orange_form,Male,41,20.1,13.7,40.6,44.5,18.0
orange_form,Male,42,20.6,14.4,42.8,46.5,19.6
orange_form,Male,43,21.0,15.0,42.9,47.2,19.4
orange_form,Male,44,21.5,15.5,45.5,49.7,20.9
orange_form,Male,45,21.6,15.4,45.7,49.7,20.6
orange_form,Male,46,21.6,14.8,43.4,48.2,20.1
orange_form,Male,47,21.9,15.7,45.4,51.0,21.1
orange_form,Male,48,22.1,15.8,44.6,49.6,20.5
orange_form,Male,49,23.0,16.8,47.2,52.1,21.5
orange_form,Male,50,23.1,15.7,47.6,52.8,21.6
orange_form,Female,1,10.7,9.7,21.4,24.0,9.8
orange_form,Female,2,11.4,9.2,21.7,24.1,9.7
orange_form,Female,3,12.5,10.0,24.1,27.0,10.9
orange_form,Female,4,12.6,11.5,25.0,28.1,11.5
orange_form,Female,5,12.9,11.2,25.8,29.1,11.9
orange_form,Female,6,14.0,11.9,27.0,31.4,12.6
orange_form,Female,7,14.0,12.8,28.8,32.4,12.7
orange_form,Female,8,14.3,12.2,28.1,31.8,12.5
orange_form,Female,9,14.7,13.2,29.6,33.4,12.9
orange_form,Female,10,14.9,13.0,30.0,33.7,13.3
orange_form,Female,11,15.0,12.3,30.1,33.3,14.0
orange_form,Female,12,15.6,13.5,31.2,35.1,14.1
orange_form,Female,13,15.6,14.0,31.6,35.3,13.8
orange_form,Female,14,15.6,14.1,31.0,34.5,13.8
orange_form,Female,15,15.7,13.6,31.0,34.8,13.8
orange_form,Female,16,16.1,13.6,31.6,36.0,14.0
orange_form,Female,17,16.1,13.7,31.4,36.1,13.9
orange_form,Female,18,16.2,14.0,31.6,35.6,13.7
orange_form,Female,19,16.7,14.3,32.3,37.0,14.7
orange_form,Female,20,17.1,14.5,33.1,37.2,14.6
orange_form,Female,21,17.5,14.3,34.5,39.6,15.6
orange_form,Female,22,17.5,14.4,34.5,39.0,16.0
orange_form,Female,23,17.5,14.7,33.3,37.6,14.6
orange_form,Female,24,17.6,14.0,34.0,38.6,15.5
orange_form,Female,25,18.0,14.9,34.7,39.5,15.7
orange_form,Female,26,18.0,16.3,37.9,43.0,17.2
orange_form,Female,27,18.3,15.7,35.1,40.5,16.1
orange_form,Female,28,18.4,15.5,35.6,40.0,15.9
orange_form,Female,29,18.4,15.7,36.5,41.6,16.4
orange_form,Female,30,18.5,14.6,37.0,42.0,16.6
orange_form,Female,31,18.6,14.5,34.7,39.4,15.0
orange_form,Female,32,18.8,15.2,35.8,40.5,16.6
orange_form,Female,33,18.9,16.7,36.3,41.7,15.3
orange_form,Female,34,19.1,16.0,37.8,42.3,16.8
orange_form,Female,35,19.1,16.3,37.9,42.6,17.2
orange_form,Female,36,19.7,16.7,39.9,43.6,18.2
orange_form,Female,37,19.9,16.6,39.4,43.9,17.9
orange_form,Female,38,19.9,17.9,40.1,46.4,17.9
orange_form,Female,39,20.0,16.7,40.4,45.1,17.7
orange_form,Female,40,20.1,17.2,39.8,44.1,18.6
orange_form,Female,41,20.3,16.0,39.4,44.1,18.0
orange_form,Female,42,20.5,17.5,40.0,45.5,19.2
orange_form,Female,43,20.6,17.5,41.5,46.2,19.2
orange_form,Female,44,20.9,16.5,39.9,44.7,17.5
orange_form,Female,45,21.3,18.4,43.8,48.4,20.0
orange_form,Female,46,21.4,18.0,41.2,46.2,18.7
orange_form,Female,47,21.7,17.1,41.7,47.2,19.6
orange_form,Female,48,21.9,17.2,42.6,47.4,19.5
orange_form,Female,49,22.5,17.2,43.0,48.7,19.8
orange_form,Female,50,23.1,20.2,46.2,52.5,21.1

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