KNN Imputer | Multivariate Imputation | Handling Missing Data Part 5

The KNN Imputer is a technique used in multivariate imputation to fill in missing values by considering the values of their k-nearest neighbors. This method leverages similarities between data points to impute missing values effectively, offering a versatile approach to handling missing data in a multivariate context. Code used: https://github.com/campusx-official/1... Documentation: https://scikit-learn.org/stable/modul... https://scikit-learn.org/stable/modul... ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in/s/store ============================ 📱 Grow with us: CampusX' LinkedIn:   / campusx-official   CampusX on Instagram for daily tips:   / campusx.official   My LinkedIn:   / nitish-singh-03412789   Discord:   / discord   E-mail us at [email protected] ⌚Time Stamps⌚ 00:00 - Intro 00:19 - Difference between Univariate and Multivariate Imputation 02:15 - How KNN Imputer works? 06:46 - NAN Euclidean Distance Documentation 14:17 - Advantages and Disadvantages of KNN Imputer 15:56 - Code Demo 20:00 - Concept of Uniform and Distance