About this document
Handling Missing Data: 6 Imputation Methods by zero is a document available to read on EtoBox.
This document discusses 6 different methods for imputing or replacing missing values in a dataset: 1. Do nothing and let algorithms handle it 2. Impute using mean or median values of each column 3. Impute using most frequent or constant values 4. Impute using k-nearest neighbors algorithm 5. Impute using linear regression 6. Impute using multivariate imputation by chained equations It provides examples of implementing mean, median, most frequent, and k-nearest neighbors imputation using Python librarie
- Author
- zero
- Language
- EN