Ram Tavva walks us through the algorithm to design decision trees:
A decision tree is made up of several nodes:
1.Root Node: A Root Node represents the entire data and the starting point of the tree. From the above example the
First Node where we are checking the first condition, whether the movie belongs to Hollywood or not that is the
Rood node from which the entire tree grows
2.Leaf Node: A Leaf Node is the end node of the tree, which can’t split into further nodes.
From the above example ‘watch movie’ and ‘Don’t watch ‘are leaf nodes.
3.Parent/Child Nodes: A Node that splits into a further node will be the parent node for the successor nodes. The
nodes which are obtained from the previous node will be child nodes for the above node.
Read on for an example of implementation in R.
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