Veri Madenciliği ve Makine Öğrenmesi ile Farklı Alanlarda Uygulamalar

This book consists of seven chapters examining the theoretical foundations and practical applications of data mining and machine learning methods in various fields. Edited by Assoc. Prof. Dr. Şenol Çelik, Assoc. Prof. Dr. Nilay Köleoğlu, and Assoc. Prof. Dr. Fatih Çemrek, the work addresses advanced statistical techniques that enable extracting meaningful information from complex data sets. The book details the working principles of algorithms such as Decision Trees (CART, CHAID, ID3, C4.5), MARS (Multivariate Adaptive Regression Splines), Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Random Forest. Application areas include livestock (yield estimation in dairy cattle, body measurements in horses), cohesion in agricultural organizations, and analysis of factors affecting traffic accidents. Additionally, it covers the use of training and test data in machine learning and Ridge Regression application. Containing both Turkish and English chapters, this study aims to guide researchers and students in the fields of statistics, biometrics, and econometrics through data analysis processes.