Skip to content

Latest commit

 

History

History
36 lines (19 loc) · 1.37 KB

README.md

File metadata and controls

36 lines (19 loc) · 1.37 KB

Assignment13-KNN

ExcelR Data Science Assignment No 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