The algorithm terminates either when all the attributes have been exhausted, or the decision tree perfectly classifies the examples. The following diagram should explain the ID3 algorithm further: 6.3 ...

finding the smallest possible decision tree is intractable in general, so we will settle for approximation algorithms that find small (but not necessarily the smallest) trees; but we also want a ...

Because the decision tree model was trained using normalized and encoded data, the x-input must be normalized and encoded in the same way. Notice the double square brackets on the x-input. The predict ...