1 Jun 2023
Imbalanced Classification: Problems & Solutions with Use Cases
During the past decade, supervised classification problems have been identified in several actuarial fields, such as risk management, projection modeling, fraud and anomaly detection, etc. In many of these problems, the respective classification task is subject to a highly imbalanced dataset, i.e., the number of instances of the relevant class is extremely small in comparison to the total number of instances. Classical supervised machine learning frameworks can be misleading (in case of using an inappropriate evaluation metric) or ineffective (in case of using inappropriate classifiers) in such situations.
In this web session, we will present several techniques to tackle these issues. More specifically, external approaches (data preprocessing, such as over- and undersampling procedures) as well as internal approaches (modification of classifiers, e.g., balanced versions of random forests and support vector machines) will be discussed. After a concise introduction to imbalanced classification and the techniques above, we will turn theory into practice by implementing entire machine learning workflows in Python and R for two real-world use cases: churn prediction and fraud detection.
Organised by the EAA – European Actuarial Academy GmbH.
This web session is designed for all actuaries that are interested in or already working on supervised classification projects and who want to enhance their professional skills in machine learning. The participants should bring basic knowledge in the field of supervised machine learning as well as in one of the programming languages Python or R. As we will practically implement machine learning workflows for the aforementioned use cases, the participants are encouraged to setup a Python or R environment on their local computer or to ensure that Jupyter Notebook collaboration platforms such as Google Colab are accessible.
Technical RequirementsPlease check with your IT department if your firewall and computer settings support web session participation (the programme Zoom will be used for this online training). Please also make sure that you are joining the web session with a stable internet connection.
Purpose and Nature