From Market Baskets to Databases: Association Rule Mining
What do the customers buy? Which products are bought together? With these two short questions the field of association rule (AR) mining makes its appearance. In this field of ML, the original aim was to find associations and correlations between the different items that customers place in their shopping market. More generally, the goal of AR is to find frequent and interesting patterns , associations , correlations , or causal structures among sets of items or elements in large databases and put these relationships in terms of association rules . AR is an important part of the unsupervised learning paradigm, so the algorithm has not the presence of an expert to teach it during the training stage. Why AR mining may be so important ? Many commercial applications generate huge amounts of unlabeled data (just think of Facebook for a moment), so our favorite classifier system will not work in this environment. With AR we can exploit such databases and extract any kind of useful in...