The document discusses the creation of a decision tree regression model using two independent variables (x1 and x2) to predict a dependent variable (y). It outlines the process of segmenting data into terminal leaves and using their averages for predictions. Additionally, it mentions utilizing R for building the regression tree without splitting the dataset, resulting in an average near 250,000.

12. Decision Tree

14. Decision Tree

15. Scatter plot
which represent
dataset.
Two
independent
variables i.e. X1
and X2
Dependent
variable is Y

16. • Split up the data into
segments

19. • How these terminal
leaves are used to
predict the value of Y
• Take the averages of
each of these terminal
leaves for Y

20. Build Regression Tree by Using R

22. No Split Take the average of Whole dataset that is near about 250000.

24. Non-Continuous Regression Model

25. For higher Resolution