AnyML Custom Metrics - Automated Machine Learning Platform скачать в хорошем качестве

AnyML Custom Metrics - Automated Machine Learning Platform

Welcome to the AnyML Video Learning Library! In this tutorial, we walk you step-by-step through creating an experiment with custom metrics—letting you define how your model is evaluated and sorted. You’ll learn how to: Access the Custom Metric Master from your profile or add a metric directly during experiment setup. Upload a tabular dataset, name your experiment, and add your metric in Advanced Settings. Define Metric Name, choose optimization direction (maximize/minimize), and implement the logic using predefined parameters (target, prediction, probabilities, classes). Understand system compatibility checks and fallback to default metrics if needed. Then, launch the experiment—which may take time depending on your dataset—and review the results: The custom metric appears in the Leaderboard, letting you rank models alongside the AnyML Score. It’s also visible in the Model Report, helping you assess which model performs best based on your custom criteria. That's it! Now you know how to integrate custom metric code into your training workflow. Let us know: should we compare experiments with and without custom metrics? Explore more in our video library. Visit our website or email us with questions. #AnyML #MachineLearning #CustomMetrics