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Applied the Random Forest model in my Regressor model both in Python and R

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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

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Applied the Random Forest model in my Regressor model both in Python and R

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