classification algorithms -machine random forest introduction random forest is supervised learning algorithm which is used for both classification as well as regression but howeverit is mainly used for classification problems as we know that forest is made up of trees and more trees means more robust forest similarlyrandom forest algorithm creates decision trees on data samples and then gets the prediction from each of them and finally selects the best solution by means of voting it is an ensemble method which is better than single decision tree because it reduces the over-fitting by averaging the result working of random forest algorithm we can understand the working of random forest algorithm with the help of following stepsstep firststart with the selection of random samples from given dataset step nextthis algorithm will construct decision tree for every sample then it will get the prediction result from every decision tree step in this stepvoting will be performed for every predicted result step at lastselect the most voted prediction result as the final prediction result