Maximum Likelihood Decision

Related lectures (30)

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Covers the likelihood ratio test for detection and estimation in statistical analysis.

Explores Generalized Linear Regression, Classification, confusion matrices, ROC curves, and noise in data.

Delves into quantifying statistical dependence through covariance, correlation, and mutual information.

Covers the properties of the exponential family and the estimation of parameters.

Explores exponential families, Bernoulli distributions, parameter estimation, and maximum entropy distributions in statistical modeling.

Covers the normal distribution, including its properties and calculations.

Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.

Covers statistical hypothesis testing, likelihood estimation, and confidence intervals construction.

Introduces the Boltzmann Machine, covering expectation consistency, data clustering, and probability distribution functions.

Covers random matrix theory and the replica method to compute quantities related to non-hermitic series using the Stieltjes transform.