You've just finished training a decision tree for spam classification, and it is getting abnormally bad performance on both your training and test sets. You know that your implementation has no bugs, so what could be causing the problem?

Machine learning (ML) is a branch of artificial intelligence that leverages data to improve computer performance by giving machines the ability to "learn", or improve performance — based on the data.

There are four basic approaches to machine learning: supervised learning, unsupervised learning, semi-supervised learning and reinforcement learning.