Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Decision model

Related lectures (31)

Discriminant Analysis: Bayes Rule

Covers the Bayes discriminant rule for allocating individuals to populations based on measurements and prior probabilities.

Perceptual Decision Making: Neuronal Dynamics MOOC: Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition

Explores competitive dynamics in perceptual decision making and neuronal responses in visual cortex V5/MT.

Decision Theory: Risk and Hypothesis Testing

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

Thermodynamic Properties: Equations and Models

Explains thermodynamic properties, equations of state, and mixture rules for energy systems modeling.

Introduction to Supervised Learning and Decision Theory

Covers supervised learning, decision theory, risk minimization, and goal achievement.

Ethics and Law of AI

Delves into ethics and law in AI, focusing on values, normative ambitions, and ethical challenges.

Distribution Estimation

Covers the estimation of distributions using samples and probability models.

Interpretable Machine Learning: Sparse Decision Trees and Interpretable Neural Networks

Explores the extremes of interpretability in machine learning, focusing on sparse decision trees and interpretable neural networks.

Optimisation in Energy Systems

Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.

Structured Classifications: Decision Trees and Boosting

Explores decision trees, overfitting elimination, boosting techniques, and their practical applications in predictive modeling.

Decision Theory: Risk and Inference

Explores decision theory, risk functions, and inference in statistical analysis.

Hypothesis Testing: State of Nature

Explores hypothesis testing, emphasizing the state of nature and the importance of choosing the most powerful test.

Maximum Likelihood Estimation

Covers Maximum Likelihood Estimation, focusing on ML Estimation-Distribution, Shrinkage Estimation, and Loss functions.

Environmental Legislation and Construction Law

Explores environmental legislation, construction law, polluted sites, and cost responsibilities.

Bayesian Inference: Optimal Estimation

Explores optimal Bayesian inference, denoising, scalar estimation, and phase transitions.

Decision and regression trees

Explores decision and regression trees, impurity measures, learning algorithms, and implementations, including conditional inference trees and tree pruning.

Neuronal Dynamics: Decisions and Simulations MOOC: Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition

Explores neuronal dynamics in decision making through simulations and experiments on populations of neurons.

Actor Failure Handling

Covers failure handling in asynchronous systems using the Actor Model and discusses supervision, resilience, and actor lifecycle.

Heat Exchanger Design

Covers the design of heat exchangers and optimization strategies for heat transfer.

Untitled