Data Science, Model Performance, Model Selection, Machine Learning, Bobrupakroy.
introducing a penalty term for the number of parameters in the model. 2. BIC: = -2 * LL + log(N) * k Where log() has the base-e called the natural logarithm, LL is the log-likelihood of the model, N is the number of examples in the training dataset, and k is the number of parameters in the model.