Machine Learning: Random Forest with Python from Scratch - How to Classify

What is the primary purpose of the recursive method in training a decision tree?

• To initialize the decision tree

• To identify and return predictions from leaf nodes

• To calculate the information gain

• To handle missing data

What is the first step in building the decision tree?

• Compiling the code

• Passing the training data

• Defining the leaf nodes

• Calculating the accuracy

Which common error is highlighted during the implementation of the decision tree?

• Infinite loops

• Memory overflow

• Undefined variables

• Incorrect data types

What was the cause of the 'leaf is not defined' error?

• A syntax error

• An incorrect function call

• A typo in the code

• A missing import statement

What does the classify method return when it reaches a leaf node?

• The node's question

• The node's predictions

• The node's true branch

• The node's false branch

What is the expected output of the classify method for the given test data?

• 3

• 1

• 0

• 2

What future improvement is planned for the decision tree model?

• Adding more training data

• Implementing an accuracy method

• Reducing the model size

• Increasing the number of nodes