Constructing A Decision Tree Using Information Gain
A decision tree can be constructed top-down using the information gain in the following way:
- begin at the root node
- determine the attribute with the highest information gain which is not already used as an ancestor node
- add a child node for each possible value of that attribute
- attach all examples to the child node where the attribute values of the examples are identical to the attribute value attached to the node
- if all examples attached to the child node can be classified uniquely add that classification to that node and mark it as leaf node
- go back to step two if there are unused attributes left, otherwise add the classification of most of the examples attached to the child node
Read more about this topic: Information Gain In Decision Trees
Famous quotes containing the words constructing, decision, tree, information and/or gain:
“The very hope of experimental philosophy, its expectation of constructing the sciences into a true philosophy of nature, is based on induction, or, if you please, the a priori presumption, that physical causation is universal; that the constitution of nature is written in its actual manifestations, and needs only to be deciphered by experimental and inductive research; that it is not a latent invisible writing, to be brought out by the magic of mental anticipation or metaphysical mediation.”
—Chauncey Wright (1830–1875)
“The women of my mother’s generation had, in the main, only one decision to make about their lives: who they would marry. From that, so much else followed: where they would live, in what sort of conditions, whether they would be happy or sad or, so often, a bit of both. There were roles and there were rules.”
—Anna Quindlen (20th century)
“You are wind in a stark tree,
you are the stark tree unbent,
you are a strung bow,
you are an arrow.”
—Hilda Doolittle (1886–1961)
“In the information age, you don’t teach philosophy as they did after feudalism. You perform it. If Aristotle were alive today he’d have a talk show.”
—Timothy Leary (b. 1920)
“What though he did not belong to your clique! Though you may not approve of his method or his principles, recognize his magnanimity. Would you not like to claim kindredship with him in that, though in no other thing he is like, or likely, to you? Do you think that you would lose your reputation so? What you lost at the spile, you would gain at the bung.”
—Henry David Thoreau (1817–1862)