Loss function

Formal sciences
Statistics
Statistical inference
Mathematical statistics

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Related lectures (129)

Linear & Weighted Regression

Covers linear and weighted regression, limitations, and introduces locally weighted regression for model-free regression.

Decision Theory: Risk and Hypothesis Testing

Covers decision theory, risk functions, and hypothesis testing in statistical inference.

Optimisation Strategies: Energy Systems Modelling and Optimization

Explores solving strategies for energy system optimization problems and different types of optimization approaches.

Maximum Likelihood Estimation: Linear Models

Explores maximum likelihood estimation in linear models, covering Gaussian noise, covariance estimation, and support vector machines for classification problems.

SVMs and Feature Maps

Explores SVMs, feature maps, and the importance of finding the maximum margin solution for classification problems.

Receiver-Operator Characteristics: ROC Curves

Explains ROC curves, Precision-Recall curve, RMSLE, and model validation.

Quantitative Risk Management: Risk Measures

Covers risk measures used in determining risk capital and insurance premiums.

Statistical Estimation: Gaussian Linear Model

Delves into statistical estimation, highlighting the Gaussian linear model and the limitations of ML estimators.

Model Evaluation: K-Nearest Neighbor

Explores model evaluation with K-Nearest Neighbor, covering optimal k selection, similarity metrics, and performance metrics for classification models.

Optimization and Simulation

Explores transformations into single-objective functions, lexicographic rules, and constrained optimization in optimization and simulation.

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