Detection of Mechanical Failure using Anomaly Detection
A comparative analysis between supervised and unsupervised methods
A Tale of Two Algorithms The APS Scania Dataset, a captivating and information-rich dataset, comes from Scania, a top-tier manufacturer of heavy trucks and buses. It was created for the Industrial Challenge at the 11th International Symposium on Intelligent Data Analysis (IDA 2012), with the primary goal of minimizing the overall cost of incorrect decisions made by truck operators when predicting failures in Air Pressure System (APS) components.
In anomaly detection, we often face the critical choice of selecting between supervised and unsupervised learning algorithms, depending on the type of anomaly we aim to detect.