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.
Keywords
Artificial neural network
German
Set (abstract data type)
Statistical classification
Key (lock)
Computer science
Artificial intelligence
Data mining
Machine learning
Subject Areas
Financial Distress and Bankruptcy Prediction
·Accounting ·Social Sciences
Imbalanced Data Classification Techniques
·Artificial Intelligence ·Physical Sciences
Credit Risk and Financial Regulations
·Finance ·Social Sciences