Description: Anomaly detection in e-commerce refers to the identification of unusual purchasing behaviors in the data generated by online transactions. This process involves the use of advanced data analysis techniques and machine learning to discern normal consumer behavior patterns and detect significant deviations that may indicate fraud, errors, or suspicious activities. Anomaly detection is crucial for maintaining the integrity of e-commerce platforms, as it allows companies to respond quickly to potential threats, optimize customer experience, and protect their revenues. The main features of this technique include the ability to process large volumes of data in real-time, adaptability to new behavior patterns, and continuous improvement through machine learning. In an environment where digital transactions are increasingly common, anomaly detection becomes an essential tool for ensuring security and trust in online commerce.
