How IDIADA optimized its intelligent chatbot with Amazon Bedrock
AWS Machine Learning Blog
FEBRUARY 25, 2025
To determine the best parameter values, we conducted a grid search with 10-fold cross-validation, using the F1 multi-class score as the evaluation metric. For the classifier, we employ SVM, using the scikit-learn Python module. The SVM algorithm requires the tuning of several parameters to achieve optimal performance.
Let's personalize your content