Data mining framework for segment prediction

Abstract

Methods and systems are presented for mining data in association with predicting occurrences of events. Upon detecting an occurrence of an event associated with a transaction, a data mining system accesses data associated with different transactions, and generates a decision tree for predicting occurrences of the event based on the data. Using a classification specification, the data mining system traverses the decision tree and prunes at least a portion of the decision tree that does not satisfy the classification specification. The data mining system then extracts data relevant to predicting occurrences of the event from the pruned decision tree. The extracted data includes attributes and/or criteria that are relevant to predicting occurrences of the event. Based on the extracted data, one or more actions can be performed to improve the event prediction process and/or reduce the frequency of the occurrences of the event.