This browser is no longer supported.
Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support.
Answer the following questions to see what you've learned.
Why did we choose a decision tree for our machine learning algorithm?
A decision tree is the most complex and accurate algorithm.
A decision tree is easy to visualize. It fits well because the model can make only two choices: yes or no.
A decision tree has lots of branches, and the model can make lots of choices.
What is the purpose of splitting your dataset?
To make your model more accurate by getting rid of bad data.
To try out different algorithms with different data.
To have different data for training and testing your model.
You must answer all questions before checking your work.
Continue
Was this page helpful?