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Concept

Decision analysis

Related lectures (32)

Linear Models for Classification: Part 3

Explores linear models for classification, including binary classification, logistic regression, decision boundaries, and support vector machines.

Likelihood Ratio Test: Detection & Estimation

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

Thermodynamic Properties: Equations and Models

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

Symbolic Representation of State Spaces

Delves into symbolic representation of state spaces using decision diagrams for high-level Petri nets, showcasing efficient encoding techniques and benchmark results.

Classification Detection

Covers binary hypothesis testing and decision functions in specific scenarios.

Advanced Machine Learning: Feature Selection

Explores machine learning algorithms, feature selection techniques like FAST and BRIEF descriptors, and the limitations of deep learning.

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.

Distribution Estimation

Covers the estimation of distributions using samples and probability models.

Optimisation in Energy Systems

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

Ethics and Law of AI

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

Linear Classification Models: From Binary to Multiclass

Explores the extension of linear classifiers to handle multiclass problems and compares their performance on various datasets.

Raising & Managing Money: Summary

Explores venture financing stages, funding analysis, sources, and burn rate importance.

Linear Classification: Signed Distance and Perceptron

Explores signed distance, perceptron, logistic regression, cross entropy, and multi-class classification.

Structured Classifications: Decision Trees and Boosting

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

Social Impact of Infrastructure Projects MOOC: Building expertise on developing sustainable and resilient infrastructure

Delves into the social impact of infrastructure projects on children and cultural heritage, using real-world examples to illustrate the challenges and importance of early consideration of social criteria.

Concept Selection and Tradespace Exploration Log in to Mediaspace to watch this video

Covers decision analysis, concept selection methods, non-dominance, and optimization in system design.

Optimal Decision Analysis Log in to Mediaspace to watch this video

Explores strong duality, complementary slackness, economic interpretation, and stochastic problem scenarios in linear programming.

Decision Tree Classification Log in to Mediaspace to watch this video

Covers decision tree classification using KNIME Analytics Platform for data preprocessing and model creation.

Supervised Learning: Formalization and Cost Functions Log in to Mediaspace to watch this video

Covers the formalism for supervised learning and decision functions in classification problems.

Support Vector Machines: Soft Margin SVM Log in to Mediaspace to watch this video

Introduces Soft Margin SVM, aiming to balance errors and margin width.