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Decision trees in Artificial intelligence

Posted on December 7, 2021December 7, 2021 By christo No Comments on Decision trees in Artificial intelligence

A decision tree reaches its decision by performing a sequence of tests. Each internal node in the tree corresponds to a test of the value of one of the input attributes, Ai, and the branches from the node are labeled with the possible values of the attribute, Ai = vik. Each leaf node in the tree specifies a value to be returned by the function. The decision tree representation is natural for humans; indeed, many “How To” manuals (e.g., for car repair) are written entirely as a single decision tree stretching over hundreds of pages

Table of Contents

  • Expressiveness of decision trees
  • Inducing decision trees from examples

Expressiveness of decision trees

A Boolean decision tree is logically equivalent to the assertion that the goal attribute is true if and only if the input attributes satisfy one of the paths leading to a leaf with value true. Writing this out in propositional logic, we have

Goal ⇔ (Path1 ∨ Path2 ∨···)

Inducing decision trees from examples

An example for a Boolean decision tree consists of an (x, y) pair, where x is a vector of values for the input attributes, and y is a single Boolean output value

 Inducing decision trees
Inducing decision trees

Artificial intelligence Tags:Artificial intelligence, Decision trees in Artificial intelligence

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