Uygulamalı Veri Madenciliği Algoritmaları Üçüncü Bölüm "Sınıflandırma"
Abstract
This chapter introduces classification problems and commonly used algorithms such as Random Forest, Logistic Regression, SVM, XGBoost, and Neural Networks. It explains performance metrics (accuracy, precision, recall, F1) and demonstrates through the German Credit Risk dataset that the advantages of different algorithms vary depending on the problem type.
Fields of Study & Subjects
Data Mining and Machine Learning Applications
Imbalanced Data Classification Techniques
Financial Distress and Bankruptcy Prediction
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 1 January 2026
- Document type
- Book chapter