Introduction to Aa 19 20 Lecture 14
If you are looking for information about Aa 19 20 Lecture 14, you have come to the right place. Bayesian Decision theory. Maximum a posteriori estimation. Decisions and costs.
Aa 19 20 Lecture 14 Comprehensive Overview
Classification. Linear separability and discriminants. Logistic Regression. Using linear classifiers in higher dimensions. Hierarchical Clustering. Agglomerative and Divisive Clustering. Fuzzy sets and clustering. Fuzzy c-means. Manifold learning. Second assignment.
Summary & Highlights for Aa 19 20 Lecture 14
- Maximum Margin Classifiers. Support vector machines for linear classification.
- Beware the people weeping, when they bear the iron hand.” Professor David Blight examines Reconstruction, in its many forms.
- Supervised learning, minimization (least squares), polynomial regression.
- Lazy learning. K-NN. Kernel regression and kernel density estimation.
- Decisions and costs.
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