Abstract
Food consumption patterns of countries by gross national income (GNI) groups are determined with a model by using GNI per capita and daily food consumption per capita data. The model was formed with data mining application, the most important stage of the knowledge discovery in databases. C5.0, one of the decision tree’s algorithms giving powerful results in SPSS Modeler, was used to form the model. According to the model, the consumption of meat, sugar and sweeteners, alcoholic beverages, eggs, pulses, vegetables, other aquatic products, fish, other starchy foods and fruits are determined to be important variables by GNI groups. It is also determined that when GNI increases, daily average consumptions per capita of meat, alcoholic beverages, vegetable oils, fish, stimulants, animal fats, fruits, offal, milk, sugar and sweeteners and eggs increase; while those of cereals and pulses decrease.