Why Choose Random Forest and Not Decision Trees

A decision tree is a simple tree-like structure constituting nodes and branches. At each node, data is split based on any of the input features, generating two or more branches as output. This iterative process increases the numbers of generated branches and partitions the original data. This continues until a node is generated where all or almost all of the data belong to the same class and further splits -- or branched -- are no longer possible. This whole process generates a tree-like structure.