What are some best practices for feature engineering?
An example of an AI chatbot conversation about feature engineering best practices.
What are some best practices for feature engineering?
Some best practices include understanding your data, handling missing values, and scaling features appropriately.
Can you explain why handling missing values is important?
Handling missing values is crucial because they can lead to biased models and inaccurate predictions.
What techniques can I use to handle missing values?
You can use techniques like imputation, removing missing data, or using algorithms that support missing values.
How do I know which features to engineer?
Start by analyzing feature importance, correlation with the target variable, and domain knowledge to guide your decisions.
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