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.
Explain common techniques for transforming categorical features into numerical formats for machine learning.
Develop a robust strategy for identifying and handling outliers in complex datasets, ensuring data integrity and reliable analysis for various business objectives.
