ExcelR_Assignment---KNN---Assignment---13

K-Nearest Neighbors (KNN) Algorithm :

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.

This assignment will study following Questions :

Question No 1 :

Prepare a model for glass classification using KNN

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

Question No 2 : Implement a KNN model to classify the animals in to categorie