| Modified by Brian Frasca (6/13/94) - Removed first attribute, | combined classes 1 and 3, and removed classes 4 through 7 | as suggested by Holte. This turns the problem into predicting | whether the window was float processed or not. | Ronny: Note that because classes 4-7 were deleted, there are less | instances than in glass. | |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: | 1. Id number: 1 to 214 | 2. RI: refractive index | 3. Na: Sodium (unit measurement: weight percent in corresponding oxide, as | are attributes 4-10) | 4. Mg: Magnesium | 5. Al: Aluminum | 6. Si: Silicon | 7. K: Potassium | 8. Ca: Calcium | 9. Ba: Barium | 10. Fe: Iron | 11. 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 | |8. 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 | |9. 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 float_processed, non_float_processed. Refractive Index: continuous Sodium: continuous Magnesium: continuous Aluminum: continuous Silicon: continuous Potassium: continuous Calcium: continuous Barium: continuous Iron: continuous