This document discusses using Lagrange interpolation to estimate missing values in datasets. It begins with an introduction to missing data problems and common techniques for handling missing values like deletion, mean substitution, and more. It then explains Lagrange interpolation, which uses known data points to estimate values at unknown points. The algorithm for Lagrange interpolation is presented. An example using years of experience and salary data to estimate salary for 10 years of experience is shown. The document concludes that Lagrange interpolation can be used to estimate missing values in preprocessing if the relationship between attributes is uniform. Limitations are noted if the relationship is not uniform.