How do I handle missing data in preprocessing?

How do I handle missing data in preprocessing?

Handling missing data is crucial for accurate analysis. You can use techniques like imputation, deletion, or using algorithms that support missing values.

What is imputation, and how do I apply it?

Imputation is the process of replacing missing values with substituted values. Common methods include mean, median, or mode substitution.

Are there any risks associated with imputation?

Yes, imputation can introduce bias if not done carefully. It's important to understand the data and the reason for missingness.

What about using algorithms that handle missing data?

Some algorithms, like decision trees, can handle missing values directly. This can be a good option if you want to avoid imputation.