Log likelihood

Introduction

When evidence is entered in a Bayesian network or Dynamic Bayesian network, the Probability (likelihood) of that evidence, denoted $P\left(e\right)$ can be calculated.

The Probability of evidence $P\left(e\right)$ indicates how likely it is that the network could have generated that data. The lower the value, the less likely.

Note: The Log Likelihood $Log\left(P\left(e\right)\right)$ is also reported, as the $P\left(e\right)$ can often report zero, due to underflow caused by the repeated multiplication of small probability values, using floating point arithmetic.

An example of zero likelihood:

Note: Log Likelihood values are often used to detect anomalous data.