Catalog Description: Classification regression, clustering, dimensionality, reduction, and density estimation. Mixture models, hierarchical models, factorial models, hidden Markov, and state space models, Markov properties, and recursive algorithms for general probabilistic inference nonparametric methods including decision trees, kernal methods, neural networks, and wavelets. Ensemble methods.

Units: 3

Also Offered As: STAT C241A, COMPSCI C281A

Related Areas:

• Artificial Intelligence (AI)
• Biosystems & Computational Biology (BIO)

Formats:
Spring: 3 hours of lecture per week
Fall: 3 hours of lecture per week

Grading Basis: Default Letter Grade; P/NP Option

Final Exam Status: No

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