Contingency Table Fit
Contingency Table Fit (CTF) measures the quality of the representation of the Joint Probability Distribution by a Bayesian network
compared to a complete (i.e., fully-connected) network
.
BayesiaLab's CTF is defined as:
where
- is the entropy of the data with the unconnected network.
- is the entropy of the data with the evaluated network.
- is the entropy of the data with the complete (i.e., fully connected) network. In the complete network, all nodes are directly connected to all other nodes. Therefore, the complete networkis an exact representation of the chain rule. As such, it does not utilize any conditional independence assumptions for representing the Joint Probability Distribution.
- is equal to 100 if the Joint Probability Distribution is represented without any approximation, i.e., the entropy of the evaluated networkis the same as that obtained with the complete network.
- is equal to 0 if the Joint Probability Distribution is represented by considering that all the variables are independent, i.e., the entropy of the evaluated network B is the same as the one obtained with the unconnected network.
- can also be negative if the parameters of networkdo not correspond to the dataset.
Last modified 1mo ago