How is a random forest model created?

Many different decision trees are used to create a random forest. The random forest puts all the trees together if the data is divided into many packages and a decision tree is created for each package of data.

How to construct a random forest model:

• Choose 'k' features at random from a total of 'm' features where k <<m
• Calculate node D using the best split point among the "k" characteristics.
• Utilize the optimum split to divide the node into daughter nodes.
• In order to complete the leaf nodes, repeat steps two and three.
• Create a forest by repeating steps one through four n times to produce n trees.