Summary

(No information yet)

License

unknown (from Weka repository)

Dependencies

Tags

arff slurped Weka

Attribute Types

Integer,Floating Point,String

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# Instances: 214 / # Attributes: 10
HDF5 (37.8 KB) XML CSV ARFF LibSVM Matlab Octave

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Original Data Format

arff

Name

Glass

Version mldata

0

Comment

1. Title: Glass Identification Database

2. Sources: (a) Creator: B. German -- Central Research Establishment Home Office Forensic Science Service Aldermaston, Reading, Berkshire RG7 4PN (b) Donor: Vina Spiehler, Ph.D., DABFT Diagnostic Products Corporation (213) 776-0180 (ext 3014) (c) Date: September, 1987

3. Past Usage: -- Rule Induction in Forensic Science -- Ian W. Evett and Ernest J. Spiehler -- Central Research Establishment Home Office Forensic Science Service Aldermaston, Reading, Berkshire RG7 4PN -- Unknown technical note number (sorry, not listed here) -- General Results: nearest neighbor held its own with respect to the rule-based system

4. Relevant Information:n Vina conducted a comparison test of her rule-based system, BEAGLE, the nearest-neighbor algorithm, and discriminant analysis. BEAGLE is a product available through VRS Consulting, Inc.; 4676 Admiralty Way, Suite 206; Marina Del Ray, CA 90292 (213) 827-7890 and FAX: -3189. In determining whether the glass was a type of "float" glass or not, the following results were obtained (# incorrect answers):

        Type of Sample                            Beagle   NN    DA
        Windows that were float processed (87)     10      12    21
        Windows that were not:            (76)     19      16    22
   

   The study of classification of types of glass was motivated by criminological investigation. At the scene of the crime, the glass left can be used as evidence...if it is correctly identified!

5. Number of Instances: 214

6. Number of Attributes: 10 (including an Id#) plus the class attribute -- all attributes are continuously valued

7. Attribute Information:

8. Id number: 1 to 214

9. RI: refractive index

10. Na: Sodium (unit measurement: weight percent in corresponding oxide, as are attributes 4-10)

11. Mg: Magnesium

12. Al: Aluminum

13. Si: Silicon

14. K: Potassium

15. Ca: Calcium

16. Ba: Barium

17. Fe: Iron

18. Type of glass: (class attribute) -- 1 building_windows_float_processed -- 2 building_windows_non_float_processed -- 3 vehicle_windows_float_processed -- 4 vehicle_windows_non_float_processed (none in this database) -- 5 containers -- 6 tableware -- 7 headlamps

19. Missing Attribute Values: None

Summary Statistics: Attribute: Min Max Mean SD Correlation with class 2. RI: 1.5112 1.5339 1.5184 0.0030 -0.1642 3. Na: 10.73 17.38 13.4079 0.8166 0.5030 4. Mg: 0 4.49 2.6845 1.4424 -0.7447 5. Al: 0.29 3.5 1.4449 0.4993 0.5988 6. Si: 69.81 75.41 72.6509 0.7745 0.1515 7. K: 0 6.21 0.4971 0.6522 -0.0100 8. Ca: 5.43 16.19 8.9570 1.4232 0.0007 9. Ba: 0 3.15 0.1750 0.4972 0.5751 10. Fe: 0 0.51 0.0570 0.0974 -0.1879

1. Class Distribution: (out of 214 total instances) -- 163 Window glass (building windows and vehicle windows) -- 87 float processed
   -- 70 building windows -- 17 vehicle windows -- 76 non-float processed -- 76 building windows -- 0 vehicle windows -- 51 Non-window glass -- 13 containers -- 9 tableware -- 29 headlamps

Relabeled values in attribute 'Type' From: '1' To: 'build wind float'
From: '2' To: 'build wind non-float' From: '3' To: 'vehic wind float'
From: '4' To: 'vehic wind non-float' From: '5' To: containers
From: '6' To: tableware
From: '7' To: headlamps

Names

RI,Na,Mg,Al,Si,K,Ca,Ba,Fe,Type,

Types

1. numeric
2. numeric
3. numeric
4. numeric
5. numeric
6. numeric
7. numeric
8. numeric
9. numeric
10. nominal:'build wind float','build wind non-float','vehic wind float','vehic wind non-float',containers,tableware,headlamps

Data (first 10 data points)

RI	Na	Mg	Al	Si	K	Ca	Ba	Fe	Type
1.51...	12.79	3.5	1.12	73.03	0	8.77	0	0	'bui...
1.51...	12.16	3.52	1.35	72.89	0	8.53	0	0	'veh...
1.51...	13.21	3.48	1.41	72.64	0	8.43	0	0	'bui...
1.51...	14.4	1.74	1.54	74.55	0	7.59	0	0	tabl...
1.53...	12.3	0.0	1.0	70.16	0	16.19	0	0	'bui...
1.51...	12.75	2.85	1.44	73.27	0	8.79	0	0	'bui...
1.51...	13.64	3.65	0.65	73.0	0	8.93	0	0	'veh...
1.51...	13.14	2.84	1.28	72.85	0	9.07	0	0	'bui...
1.51...	14.14	0.0	2.68	73.39	0	9.07	0	0	head...
1.51...	13.19	3.9	1.3	72.33	0	8.44	0	0	'bui...
...	...	...	...	...	...	...	...	...	...

Description

A jarfile containing 37 classification problems, originally obtained from the UCI repository (datasets-UCI.jar, 1,190,961 Bytes).

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Data Source

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

Measurement Details

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revision 1

by mldata on 2010-11-06 09:57

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