Automatic Machine Learning Model Selection

Automatic Machine Learning Model Selection refers to the process of picking the optimal model from multiple candidate models through automated means. Its goal is to enhance the efficiency and accuracy of model selection while minimizing human intervention, ensuring that the selected model performs best on specific tasks. This method holds significant application value in data science and machine learning projects, as it can accelerate the model development cycle, optimize resource utilization, and improve prediction accuracy and decision support capabilities.