Exploring Aa 19 20 Lecture 7
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- Classification. Linear separability and discriminants. Logistic Regression. Using linear classifiers in higher dimensions.
- Introduction.
- Supervised learning, minimization (least squares), polynomial regression.
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In-Depth Information on Aa 19 20 Lecture 7
Generative models: naive bayes, bayes. Comparing classifiers. Fuzzy sets and clustering. Fuzzy c-means. Manifold learning. Second assignment. Introduction to clustering. K-means and k-medoids. Expectation maximization. Hierarchical Clustering. Agglomerative and Divisive Clustering.
Lecture #7
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