ExcelR Data Science Assignment No 13
K-nearest neighbors (KNN) algorithm is a type of supervised ML algorithm which can be used for both classification as well as regression predictive problems. However, it is mainly used for classification predictive problems in industry. The following two properties would define KNN well.
• Lazy learning algorithm :
KNN is a lazy learning algorithm because it does not have a specialized training phase and uses all the data for training while classification.
• Non-parametric learning algorithm :
KNN is also a non-parametric learning algorithm because it doesn’t assume anything about the underlying data.
Data Description :
RI : refractive index ... Na: Sodium ... Mg: Magnesium
AI: Aluminum ... Si: Silicon ... K: Potassium
Ca: Calcium ... Ba: Barium ... Fe: Iron
Type: 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