Log-likelihood is the logarithm of the likelihood function, which measures how well a statistical model explains the observed data given certain parameters. By taking the logarithm, calculations become more manageable and numerical stability is improved, especially when dealing with probabilities that can become very small. This transformation helps in estimating model parameters using methods like Maximum Likelihood Estimation (MLE).
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