Ckassification with support vector machines and logistic regression: the example of Turkey's import and export

In this study, foreign trade data of Turkey and machine learning methods were used and classification study was carried out. Within the scope of the study, model performance comparison was made by using support vector machines and logistic regression models from machine learning methods. Radial and linear kernel functions are used in support vector machines. Confusion matrix values and ROC curve were used to select the best classifier. The best result was obtained from the support vector machine, the radial kernel function. Key Words: Machine Learning, Support Vector Machines, Lojistic Regression, ROC Curve, Confusion Matrix, Classification