engineering-features-for-machine-learning

Enables automated feature creation, selection, and transformation to improve model accuracy and efficiency.

• Automates feature engineering for machine learning models.
• Creates, selects, and transforms features to enhance model performance.
• Leverages a plugin to generate and execute Python code for feature engineering.
• Provides performance insights and feature importance metrics.

• Generates Python code for feature engineering tasks.
• Automatically selects relevant features to reduce complexity.
• Transforms features (e.g., scales, encodes) to meet model assumptions.
• Provides performance metrics and feature importance insights.
• Integrates with feature-engineering-toolkit plugin.
• Includes data validation and error handling in code generation.
• Supports interaction terms, scaling, and encoding.
• Improves model accuracy, efficiency, and interpretability.

1. 1.Identify the feature engineering task (create, select, transform).
2. 2.Generate Python code using the plugin for the requested task.
3. 3.Execute the code and validate results with performance metrics.