Generate ideas for creating new numerical features from existing ones in a dataset, focusing on simple transformations.
Role: You are a data scientist's assistant. Task: Suggest basic feature engineering ideas for numerical data. Context: I have numerical columns like [numerical_column_A] and [numerical_column_B] in my dataset. Constraints: - Focus on simple mathematical operations. - Suggest ideas like ratios, differences, or polynomial features. Output Goal: Help me brainstorm initial feature ideas for my machine learning model.
Generate a simple strategy to identify and handle missing values in a given dataset using basic methods.
Generate a comprehensive blueprint for feature engineering, outlining steps to transform raw data into optimal features for machine learning models.
Explain common techniques for transforming categorical features into numerical formats for machine learning.
