Introduction. Mohammad Beigi Department of Biomedical Engineering Isfahan University [email protected] Pattern recognition and Machine Learning. Syllabus Introduction, Linear Models for classification Neural Networks (MLP, RBF, SOM, LVQ, ADALINE)
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Humans have developed highly sophisticated skills for sensing their environment and taking actions according to what they observe, e.g
Understanding spoken words
distinguishing fresh food from its smell
We would like to give similar capabilities to machines
are modeled and recognized in nature when we develop
pattern recognition algorithms.
understanding and appreciation for pattern recognition
systems in nature.
numerical and do not have any correspondence in natural
Figure 9: Clustering of Microarray Data
Figure 10: Brain Control Interface
Root-Mean-Square (RMS) Error:
Penalize large coefficient values
Shrinkage: reduce the order of method
Optimization Problem: Finding optimum
28*28 Pixel image : 784 real numbers, training set: