Discuss the importance of data : The Data set for Classification problem

The video tutorial explains how to build a classification tree using a data set similar to one used for a regression tree. The focus is on predicting whether a movie will win an Oscar based on various variables. The data set includes information on 506 movies, detailing whether they won an Oscar. The process involves splitting the data into training and testing sets to evaluate the model's performance. The model can then predict Oscar wins by inputting relevant variables.

What is the main goal of the classification tree in this context?

How does the data set used for the classification tree differ from the one used for the regression tree?

What specific information do we already know about the movies in this data set?

What are the two parts into which the data will be split for training the model?

How can the model be used after it has been created?