log-likelihood

Log-likelihood is a measure used in statistics to evaluate how well a model explains observed data. It reflects the probability of observing the data given the model's assumptions, expressed in logarithmic form for easier calculation. A higher log-likelihood indicates that the model more accurately captures the pattern of the data. For example, if you’re trying to predict the likelihood of certain outcomes based on your model, the log-likelihood quantifies how likely those observed outcomes are under the model’s parameters. It’s a key concept in statistical inference, helping to compare and improve models.