Walle
Created page with "{{see also|Machine learning terms}} ==Cross-validation in Machine Learning== Cross-validation is a widely used technique in machine learning for estimating the performance of a predictive model. It aims to assess how well a model can generalize to an independent dataset by evaluating its performance on multiple subsets of the training data. This approach helps to mitigate overfitting, a common issue in machine learning where the model learns the training data too wel..."
