ECE 277: PATTERN RECOGNITION
University of California, Santa Barbara
Principles and design of pattern recognition systems. Statistical classifiers: discriminant functions; bayes, minimum risk, k-nearest neighbors, perceptrons. Clustering and estimation; criteria; k-means, fuzzy, hierarchal, graph- theoretic, simulated and determininstic annealing; maximum likelihood and bayesian methods: nonparametric methods. Overview of applications.
Average GPA: 3.73
Grade distribution records: 180 students across 6 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 14 | 7.8% |
| A | 80 | 44.4% |
| A- | 43 | 23.9% |
| B+ | 30 | 16.7% |
| B | 11 | 6.1% |
| B- | 1 | 0.6% |
| C+ | 1 | 0.6% |
Based on 180 student grade records across 6 terms and 1 professor.
Instructors
- Rose K 180 students, Average GPA 3.73