What is the Purpose of Cross-Validation in Machine Learning?
In the fast-moving world of machine learning, it’s essential to ensure that models are accurate, dependable, and capable of adapting to new data. Cross-validation is a key technique that helps achieve these goals. It’s a crucial step for assessing how well machine learning models perform and for avoiding common issues like overfitting or underfitting.
What is Cross-Validation?
Cross-validation is a statistical method used to evaluate the performance of machine learning models. Visit- https://www.sevenmentor.com/ma....chine-learning-cours
Like
Comment
Share
