Akademik Dersler - İçerik

Understands basic structure of pattern recognition systems.
Summarizes execution of a pattern recognition system.
Expresses principal units within a pattern recognition system.
Defines the relationship between pattern and feature.
Explains supervised and unsupervised pattern recognition approaches.
Explains pattern classifiers.
Recognizes classifiers based on Bayes decision theory.
Recognizes linear classifiers.
Recognizes nonlinear classifiers.
Defines feature extraction approaches for popular pattern recognition applications.
Realizes feature extraction for speech recognition applications.
Realizes feature extraction for text classification applications.
Realizes feature extraction for image recognition applications.
Defines feature selection methods.
Realizes filter based feature selection process.
Realizes wrapper based feature selection process.
Analyzes the success of a feature recognition system.
Defines the relationship between training and test dataset.
Expresses contents of the confusion matrix.
Calculates classification error.