Machine Learning: Random Forest with Python from Scratch - How Decision Trees and Random Forest Work

The video tutorial explains the process of using random samples from a dataset to construct decision trees, obtain predictions, and perform a voting process to determine the final prediction. It highlights the importance of using an odd number of trees to avoid ties in voting. The tutorial concludes with a brief mention of future topics, including the pros and cons of the algorithm and when to use random forests.

How does the structure of a decision tree affect its predictions?

Why is it important to select an odd number of trees in the voting process?

Summarize the overall process of generating predictions using random samples and decision trees.