Random Forest in the Parliament!
The Random Forest Classifier is one of the most-used and talked-of algorithms in Data Science and Machine Learning and justly so! Firstly, this algorithm is so intuitive that users and even laymen (non-technical associates or stakeholders) understand how it works with extreme ease. This is so because the components in a Random Forest which are essentially decision trees, mirror the decision-making technique of humans very closely - the traditional if-and-else process! It can be stated with a high degree of confidence that most of us have used a decision tree in our lives, with or without code. Secondly, the Random Forest, being a collection of several independent classification models or decision trees, serve as an extremely robust method to arrive at any decision. To understand how a random forest works, one need only be slightly imaginative. Imagine a group of voters in a parliament house scenario . The speaker proposes a question or bill and the objective
