yctmodel 2.1.2

ModelSelector automates ensemble pipeline creation with optimized hyperparameters.

ModelSelector

The ModelSelector class is a comprehensive tool designed to simplify the model selection process in machine learning. It automates the creation of an ensemble pipeline containing a selected number of models, optimizing hyperparameters for optimal prediction scores.

Features

• Automated Ensemble Creation: The ModelSelector class automatically generates an ensemble pipeline with a specified number of models, each contributing to the final predictions.
• Hyperparameter Optimization: Utilizes a combination of model selection and hyperparameter tuning to output the best-performing models and their corresponding hyperparameters.
• Versatile Usage: Offers both automatic ensemble creation (start()) and the option to fine-tune an existing pipeline with a specific model (auto_tuning()).
• Supports Classification and Regression: Adaptable for both classification and regression tasks, providing flexibility in application.
• Easy Retrieval of Best Pipeline: Use the get_pipeline() function to retrieve the optimized pipeline with the best-performing models.

Installation

You can install the ModelSelector class using pip:

pip install yctmodel