Formulae
The algorithms that are used for constructing decision trees usually work top-down by choosing a variable at each step that is the next best variable to use in splitting the set of items. "Best" is defined by how well the variable splits the set into homogeneous subsets that have the same value of the target variable. Different algorithms use different formulae for measuring "best". This section presents a few of the most common formulae. These formulae are applied to each candidate subset, and the resulting values are combined (e.g., averaged) to provide a measure of the quality of the split.
Read more about this topic: Decision Tree Learning
Famous quotes containing the word formulae:
“I don’t believe in providence and fate, as a technologist I am used to reckoning with the formulae of probability.”
—Max Frisch (1911–1991)