Topic 3: I

Notes

Topic 3: Introduction to Data Preparation Instructor: Dr. Akash Gupta Table of contents 1 Introduction to Data Preparation 2 2 Handling Missing Values 3 2.1 Point Value Approaches . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 K-Nearest Neighbors (KNN) . . . . . . . . . . . . . . . . . . . . . 4 2.3 Multivariate Imputation by Chained Equations (MICE) . . . . . . . . 5 3 Handling Duplicates 7 4 Data Encoding 8 4.1 One-Hot Encoding . . . . . . . . . . . . . . . . . . . . . . . . . . 8 4.2 Label Encoding . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 5 Data Transformation 10 5.1 Logarithmic Transformation . . . . . . . . . . . . . . . . . . . . . 10 5.2 Square Root Transformation . . . . . . . . . . . . . . . . . . . . . 11 5.3 Box-Cox Transformation . . . . . . . . . . . . . . . . . . . . . . . 12 5.4 Data Binning . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 6 Data Scaling 15 6.1 Min-Max Scaling (Normalization) . . . . . . . . . . . . . . . . . . 16 6.2 Z-score (Standardization) . . . . . . . . . . . . . . . . . . . . . . 17 6.3 Differences between Normalization and Standardization . . . . . . . 19 7 Variable Selection 20 7.1 Forward Elimination . . . . . ...