It then modifies the model accordingly. Through methods like classification, regression, prediction and gradient boosting, supervised learning uses patterns to predict the values of the label je additional unlabeled data. Supervised learning is commonly used in applications where historical data predicts likely adjacente events. For example, it can anticipate when https://normanz109mao5.blogdemls.com/profile