Today I learnt about decision trees. Decision trees are algorithms that classify things according to their features. To train the machine, a set of training data is used. Then, a set of unseen testing data is used to check to see if the algorithm works. What I did today was classify a group of monkeys into biting and non-biting monkeys by identifying each of their features. Then I wrote out a decision tree to test another set of monkeys to see if they were biting or not. To make the decision process faster, I put the most obvious features of a biting monkey at the top of the tree.
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