How do I preprocess data for regression analysis?

How do I preprocess data for regression analysis?

Preprocessing data for regression involves several steps like handling missing values, encoding categorical variables, and scaling features.

What techniques can I use to handle missing values?

You can use techniques like mean/mode imputation, interpolation, or even removing rows with missing values, depending on the context.

Should I normalize or standardize my data?

It depends on the algorithm you're using. Standardization is often preferred for algorithms that assume normally distributed data, while normalization is useful for algorithms that require bounded input.

How do I encode categorical variables?

You can use techniques like one-hot encoding or label encoding. One-hot encoding is generally preferred for nominal categories.