Exploring Aa 18 19 Lecture 14
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- Classification. Linear separability and discriminants. Logistic Regression. Using linear classifiers in higher dimensions.
- Introduction.
- Graphical methods, Hidden markov models. The Baum-Welch and Vitterbi algorithms.
- Dial In is a devotional series with the intention of helping followers of Christ understand God's word and love Him more. Jonny ...
- Overfitting and regularization with polynomial regression. Select models: Train, validate, test.
In-Depth Information on Aa 18 19 Lecture 14
Decisions and costs. Dimensionality reduction: feature extraction with PCA; self-organzing maps. Hierarchical Clustering. Agglomerative and Divisive Clustering. Clustering Features. John
Supervised learning, minimization (least squares), polynomial regression.
That wraps up our extensive overview of Aa 18 19 Lecture 14.