Random Forest in 7 minutes

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Want to learn why Random Forests are one of the most popular and most powerful supervised Machine Learning algorithm in Machine Learning? What this video tutorial explaining the basics of Random Forests.

Hey Guys, and welcome to another Fun and Easy Machine Learning Algorithm on Random Forests.

Random forest algorithm is a one of the most popular and most powerful supervised Machine Learning algorithm in Machine Learning that is capable of performing both regression and classification tasks. As the name suggest, this algorithm creates the forest with a number of decision trees.
In general, the more trees in the forest the more robust the prediction. In the same way in the random forest classifier, the higher the number of trees in the forest gives the high accuracy results.

To model multiple decision trees to create the forest you are not going to use the same method of constructing the decision with information gain or gini index approach, amongst other algorithms. If you are not aware of the concepts of decision tree classifier, Please check out my lecture here on Decision Tree CART for Machine learning. You will need to know how the decision tree classifier works before you can learn the working nature of the random forest algorithm.

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0:00 Introduction
1:00 HOW DOES IT WORK
2:00 DISADVANTAGES
2:36 APPLICATIONS OF RANDOM FORESTS
3:43 RANDOM FOREST PSEUDOCODE
4:43 EXAMPLE
6:19 TERMS AND DEFINITIONS