Final answer:
The most suitable data mining task for identifying unusual spending at an e-commerce store is b. anomaly detection. It identifies patterns that deviate from the norm, which can be vital for detecting fraudulent activities.
Step-by-step explanation:
Analyzing the given scenario of identifying an unexpected or unusual amount of spending at an e-commerce store, the most suitable data mining task is anomaly detection. Anomaly detection focuses on identifying patterns in data that do not conform to expected behavior and are outliers compared to the majority of the data. This is particularly useful in applications such as fraud detection, where one needs to find abnormal spending behavior or transactions among a large set of data.
For this task, you would typically need to collect data on the usual spending patterns of consumers, such as purchase history, frequency of transactions, and the amounts spent. Factors that could explain the anomalies could include uncharacteristic user behavior or external factors affecting spending.