Farklı Ölçek Seviyelerindeki Değişkenlerin Analizinde Kısıtlı Ordinasyon Yöntemlerinin Başarısı

Events in nature occur with the effect of many interrelated variables, either separately or together. It is important to introduce and use methods used for analysis data sets at different scale levels linear nonlinear relationship structure between variables. Redundacy Analysis Canonical Correspondence are among such data. Aforementioned techniques generally carried out by ecologists there limited studies field health. In study, application was performed a set Cardiology including variables their performances were compared. Determination Coefficient (R2) MAPE (Mean Absolute Percentage Error) value calculated as performance criteria. According results, it seen that CCA RDA, which analyze structures types (cardiological set), explain variation sufficiently. Also, emphasized both classify well low (less than 10%) perform ordination diagram. addition, has been observed restricted diagram models give satisfactory results determining relationships coronary heart disease so they can be health too.