In simple terms, it is a process of measuring the accuracy and precision of an ML model. It helps us determine how well our models can generalize from known data points to unseen ones. By understanding how our models perform on unseen data, we can make more informed decisions about which model yields better results for our specific use case.
Model selection involves selecting an ML model that fits the data best. It considers several factors, such as which model has the highest accuracy, which model can handle large amounts of data, and which model will provide predictions with minimal bias.
We use our evaluation metrics to select the models that perform best on unseen data.
Accurate and precise machine learning models are essential for decision-making in today’s world. That is why at VirtuousAI, we strive to provide state-of-the-art model evaluation and selection services to our clients so they can confidently make reliable decisions.
Contact us today to learn how we can help you evaluate and select the right ML models for your specific use case.