Selected Topics in Pattern Recognition
The course is not on the list Without time-table
Code | Completion | Credits | Range | Language |
---|---|---|---|---|
XP33ROZ | ZK | 4 | 2P+2S | Czech |
- Course guarantor:
- Lecturer:
- Tutor:
- Supervisor:
- Department of Cybernetics
- Synopsis:
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Prerequisites: basic course in pattern recognition (e.g. P33ROD, 33RPZ).
Selected topics: Anderson's problem, Kozince algorithm, kernel perceptron,
nonlinear Fisher discriminant. Vapnik's learning theorz. Deterministic
learning. Unsupervised learning: Robbins algorithm and emprirical Bayesian
approach. Expectation-minimization algorithm. Recognition of sequences and
directed acyclic graphs. Markov models. Combination of weak classifiers:
boosting and bagging. AdaBoost.
- Requirements:
- Syllabus of lectures:
- Syllabus of tutorials:
- Study Objective:
- Study materials:
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Duda, Richard O.; Hart, Peter E.; Stork, David G.: Pattern Classification,
John Wiley, 2001
- Note:
- Further information:
- No time-table has been prepared for this course
- The course is a part of the following study plans:
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- Doctoral studies, daily studies (compulsory elective course)
- Doctoral studies, combined studies (compulsory elective course)
- Doctoral studies, structured daily studies (compulsory elective course)
- Doctoral studies, structured combined studies (compulsory elective course)