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In this study, in order to diagnose congestive heart failure (CHF) patients, second-order difference map (SDOP) features obtained from raw electrocardiogram (EEG) data is used. CHF and normal patients' electrocardiogram data, which are distributed freely via internet, is analyzed. By U-matrix presentation of Self-Organized Maps, distances between groups and clusters are examined. 1×16 sixed SODP features of raw EEG data obtained from normal and CHF patients can successfully be classified using U-matrix presentation of SOM. As a classifier Neural Network based classifier is applied and %99.9 over all accuracy performance is reached.

The aim of study is creating a new database which contains fish species and classifing this fish species. A new fish database was created by using the fish photos in seas of Turkey. The new feature set are obtained by marking the biometric points on fish to identify family and species of fishes. The features were obtained by using the three different biometric measurement techniques (Euclidean network technique, quadratic network technique, triangulation technique). A classificatios system was created by using Naive Bayesian classifier. The obtained accuracy is 93.10% for 7 families on family classification and 75.71% for 15 species on species classification.