Decision tree learning: Basic idea : <p>As given in the textbook <strong>Machine Learning</strong> by <em>Tom M. Mitchell</em>, the first statement about decision tree states that, "Decision tree leaning is a method for approximating discrete valued functions". Could someone kindly elaborate this statement, probably even justify it with an example. Thanks in advance :) :) </p>
