gini index 1
Gini Index For Decision Trees
Decision trees are often used while implementing machine learning algorithms. The hierarchical structure of a decision tree leads us to the final outcome by traversing through the nodes of the tree. Each node consists of an attribute or feature which is further split into more nodes as we move down the tree. But how do we decide which attribute/feature should be placed at the root node, which features will act as internal nodes or leaf nodes? To decide this, and how to split the tree, we use splitting measures like Gini Index, Information Gain, etc.