Random-Forest-Classifier with Ensemble Method Bagging and Boosting techniques (RAndom Forest Classifier, Bagging Classifier, ADABoosting Classifier, and XGBoost)
A multiclass classifiaction problem for the glass type classification.
Dataset: Glass Type Classification
Author: Prasad Desai
RI feature is a refractive index of the glass, and other features are the sample of the contents used to make a glass, based on the samples of contents the type of the glass is decided and classified for what purpose the glass is made. All the features are in the numerical format and the target features type of the glass contains different values it is a multiclass classification.
- RI : refractive index
- Na : Sodium (unit measurement: weight percent in corresponding oxide, as are attributes 4-10)
- Mg : Magnesium
- AI : Aluminum
- Si : Silicon
- K : Potassium
- Ca : Calcium
- Ba : Barium
- Fe : Iron
| Target Feature (Glass Type) | Classification |
|---|---|
| 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 |