After completion of this seminar, a student is expected to be able to:
- know popular biometric data types for identification.
- understand definition of data mining and the whole procedure.
- know some main methods of pattern classification.
- be able to evaluate the effect of identification methods and result.

Contents of the seminar:

Biometric data sources: fingerprints, face and iris images. Data Preprocessing, data mining which includes analysis, classification and clustering, data evaluation and interpretation. Simple classification methods: K-NN, Linear discriminate, naive Bayes rule etc. Four Rates (TPR, FNR, TNR and FNR) and Equal error rate in biometric statistic.

Modes of Study:  Compulsorily attending seminar sessions and individual or group presentation.

This seminar is accepted as advanced studies in

• Computational Methods and Programming (laskentamenetelmien ja ohjelmoinnin opintosuunta) and
• Advanced courses in Algorithmics (algoritmiikan maisteriohjelma)
• Advanced Studies in Statistics