Training data is initially provided to a supervised learning algorithm.
This may, for example, be a data record that contains transactions that are identified as fraudulent or not fraudulent.
From this, the algorithm can deduce general rules for classification and thereby identify new records according to the same pattern.
Analysis of high-dimensional data
Large data packets are increasingly high-dimensional. However, it is difficult to interpret such complex data.