What is a Random Forest and Decision Tree Classification? - Printable Version +- Forums (https://bdn.bdb.ai) +-- Forum: BDB Knowledge Base (https://bdn.bdb.ai/forumdisplay.php?fid=13) +--- Forum: DS Labs (https://bdn.bdb.ai/forumdisplay.php?fid=61) +---- Forum: DS- Lab Q&A (https://bdn.bdb.ai/forumdisplay.php?fid=63) +---- Thread: What is a Random Forest and Decision Tree Classification? (/showthread.php?tid=482)

What is a Random Forest and Decision Tree Classification? - abhishek_acharya - 12-23-2022 Random Forest A Random Forest is a supervised machine learning algorithm that is generally used for classification problems. It operates by constructing multiple decision trees during the training phase. The random forest chooses the decision of the majority of the trees as the final decision.  Decision Tree A Decision tree build classification (or regression) models as a tree structure, with datasets broken up into ever-smaller subsets while developing the decision tree, literally in a tree-like way with branches and nodes. Decision trees can handle both categorical and numerical data.