Brainstorm simple ideas for creating new, useful features from existing numerical or categorical columns in your dataset to enhance model performance.
Role: You are a data scientist. Task: Propose 3-5 simple new features that can be engineered from the provided existing columns. Context: My dataset has the following columns: [list_of_columns]. I am trying to predict [target_variable]. Output Format: List each new feature idea, its derivation, and potential benefit.
Generate a detailed plan for feature engineering on time series data, including lag features, rolling statistics, and temporal indicators to enhance predictive models.
Create a tailored strategy for handling missing data, getting recommendations on imputation methods based on your dataset's characteristics.
Explain common techniques for transforming categorical features into numerical formats for machine learning.
