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Decision Trees:
Visualize you only ever do four things at the weekend such as go shopping or watch a movie or play tennis and just stay in. In such case what you do depends on three things as: the weather or windy, rainy or sunny; means how much money you have rich or poor and where your parents are visiting. However you say to yourself as: there if my parents are visiting than we'll go to the cinema. And if they're not visiting or it's sunny so I'll play tennis further then if it's windy, and I'm rich, then I'll go shopping. Hence if they're not visiting so it's windy and I'm poor and I will go to the cinema. But if they're not visiting and it's rainy so I'll stay in.
Always memorize all this as you draw a flowchart that will enable you to read off your decision. And now if we call such diagrams decision trees. Then a suitable decision tree for the weekend decision choices would be as follows:
However we can justified by see that why such diagrams are called trees is just because of them, are admittedly upside down and they start from a root and have branches leading to leaves as the tips of the graph at the bottom. There is one important notice that the leaves are always decisions then a particular decision might be at the end of multiple branches like an example where we could choose to go to the cinema for two different reasons.
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Arbitrary categorisation - learning decision trees: Through visualising a set of boxes with some balls in. There if all the balls were in a single box so this would be nicely
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