Handling Missing Values

48 min
Block 5 — Data cleaning
Objective
choose a treatment for missing values from the missingness mechanism, the variable type and the observed rate; master deletion, simple imputation, temporal-neighborhood filling, model-based imputation and the missingness indicator; apply without exception the rule that every imputation statistic is estimated on the training set alone.
Estimated duration
50 minutes
Prerequisites
chapters 014 (descriptive statistics) and 018 (missing values); the notion of a train/test split (chapter 026)
Associated quizzes
019.1-quiz-deletion.md to 019.7-quiz-decision-table.md

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This lesson is part of the “Cleaning the Data” module

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