Exploring Aa 19 20 Lecture 13
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- Perceptron and Multilayer Perceptron.
- Hierarchical Clustering. Agglomerative and Divisive Clustering.
- This week we look at: Transitioning from First Time Abate (FTA) to Automatic Exemption from Penalty (AEP) Strict Enforcement of ...
- Affinity Propagation clustering and problems with prototype-based clustering. Density Clustering. Clustering validation.
- Introduction to unsupervised learning. Data visualization and feature selection.
In-Depth Information on Aa 19 20 Lecture 13
Empirical Risk Minimization. Decision theory. Probably Approximately Correct Learning. VC dimension and shattering. Bayesian Decision theory. Maximum a posteriori estimation. Decisions and costs. Irrepressible or Needless/Slavery or States' Rights? What Caused the Civil War? In this DeVane Fuzzy sets and clustering. Fuzzy c-means. Manifold learning. Second assignment.
Classification. Linear separability and discriminants. Logistic Regression. Using linear classifiers in higher dimensions.
That wraps up our extensive overview of Aa 19 20 Lecture 13.