In this topic we would implement Random Forest Regression, using Python. We would try to understand practical application of Random Forest and codes used for regression. As we have understood in our previous topic a random forest regression is a group of decision trees.
Step 1: Import the Libraries. We would use three libraries for this analysis:
- numpy
- pyplot
- pandas
Use below command to import the libraries.
Step 2: Import the data set.
Step 3: Fitting Random Forest Regression to the data set
Step 4: Predicting a new result
Step 5: Visualizing the Random Forest Regression results