Skip to content

Implementing K Nearest Neighbours Algorithm on Wisconsin Breast Cancer Dataset(WBCD) without using built in function for KNN algorithm. The data is split into 3 : train, validation and test data. The performance metrics are calculated for different K values.

Notifications You must be signed in to change notification settings

ShreenidhiN/KNN-Algorithm-from-Scratch

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 

Repository files navigation

KNN-Algorithm-from-Scratch

Implementing K Nearest Neighbours Algorithm on Wisconsin Breast Cancer Dataset(WBCD) without using built in function for KNN algorithm. The data is split into 3 : train, validation and test data. The performance metrics are calculated for different K values.

About

Implementing K Nearest Neighbours Algorithm on Wisconsin Breast Cancer Dataset(WBCD) without using built in function for KNN algorithm. The data is split into 3 : train, validation and test data. The performance metrics are calculated for different K values.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published