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.
Explain common techniques for transforming categorical features into numerical formats for machine learning.
Generate ideas for creating new numerical features from existing ones in a dataset, focusing on simple transformations.
