Random-Forest-Regression

Multiple Trees make a Forest. In this kind of Ensemble learning the steps To be followed are :

• Pick at random K data points from the training set
• Build decision trees associated with these trees
• Choose the number N Tree of trees you want to build & repeat steps 1 & 2
• For new data point , make each one of your N Trees predict the value of Y to for the data point in question and assign the new data point the average across all of the predicted Y values.

This is my favorite kind of Model . And as you already know - Microsoft Kinect uses Random Forest -

Link to the Awesome Paper here