Classification of Historical Anatolian Coins with Machine Learning Algorithms

To find out which period the historical coins belong to requires a number of scientific procedures that archaeologists or expertscan do. These operations can often be time-consuming and demanding operations. From this point on, in this study, theautomatically classification of historical coins by using machine learning methods is discussed. Being able to use machine learningmethods to classify historical coins can help experts and can become an analysis tool without the need for scientific tests fornon-experts. For this purpose, some physical properties of different coins used in Anatolian geography were collected andclassified by various machine learning methods named SVM, Random Forest, Bagging, and Decision Trees. Also, two differentmissing values strategies are deployed in conjunction with each chosen method. Based on our findings, random forest methodtogether with imputing missing values with mean gives an acceptable results with the accuracy rate of %71, although there aresome limitations such as high rate of missing values and working with a small dataset