Assessment of Alternative International Organizations For Turkey Using Machine Learning Algorithms

Authors : Ömer Çağrı Yavuz

Pages : 573-584

Doi:10.18185/erzifbed.1534385

View : 72 | Download : 59

Publication Date : 2024-08-31

Article Type : Research Paper

Abstract :The distribution of power balances among countries has led states to become part of an international system based on principles of territorial integrity, sovereignty, and independence. Turkey\'s process of joining the EU dating back to 1959 has been supported by various reforms and adaptation packages. However, the failure to conclude the lengthy negotiations has prompted Turkey to turn towards different organizations. Turkey, which has not fully given up its membership in the EU recently, is being considered for membership in alternative organizations, especially the SCO. Within the scope of this study, a dataset encompassing various indicators of 34 countries was created to evaluate Turkey\'s proximity to EU and SCO member countries. Subsequently, the generated dataset was grouped based on various indicators. In these applications, performance metrics were examined by positioning Turkey according to two different classes, including EU and SCO member countries, depending on various indicators.
Keywords : European Union, Shanghai Cooperation Organization, machine learning, classification