Random Forest in Python under 8 minutes скачать в хорошем качестве

Random Forest in Python under 8 minutes

To access my secret discount portal: https://linktr.ee/diogoalvesderesende New course on Zero To Mastery Academy: https://academy.zerotomastery.io/a/af... Random forests or random decision forests are an ensemble learning method for classification, regression, and other tasks that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification) or mean/average prediction (regression) of the individual trees. Random decision forests correct for decision trees' habit of overfitting to their training set. Random forests generally outperform decision trees, but their accuracy is lower than gradient boosted trees. However, data characteristics can affect their performance. Random forests are frequently used as "black box" models in businesses, as they generate reasonable predictions across a wide range of data while requiring little configuration in packages such as scikit-learn.