Features in many real world applications such as Cheminformatics, Bioinformatics and Information Retrieval have complex internal structure. For example, frequent patterns mined fr...
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Frequent itemset mining assists the data mining practitioner in searching for strongly associated items (and transactions) in large transaction databases. Since the number of frequ...
Decision tree induction algorithms scale well to large datasets for their univariate and divide-and-conquer approach. However, they may fail in discovering effective knowledge when...
Giovanni Giuffrida, Wesley W. Chu, Dominique M. Ha...
Recurring events are short temporal patterns that consist of multiple instances in the target database. Without any a priori knowledge of the recurring events, in terms of their le...