Browse all content tagged with Probability
Log loss, or logarithmic/cross-entropy loss, is a key metric to evaluate machine learning model performance—especially for binary classification—by measuring the divergence between predicted probabilities and actual outcomes, penalizing incorrect or overconfident predictions.
Monte Carlo Methods are computational algorithms using repeated random sampling to solve complex, often deterministic problems. Widely used in finance, engineering, AI, and more, they allow modeling of uncertainty, optimization, and risk assessment by simulating numerous scenarios and analyzing probabilistic outcomes.
