Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
Surveillance systems have long been used to monitor industrial processes and are becoming increasingly popular in public health and anti-terrorism applications. Most early detecti...
We develop a method to forecast stock keeping unit sales that is accurate, transparent and consistent in handling similar situations. We leverage the marketing literature to define...
In a world where massive amounts of data are recorded on a large scale we need data mining technologies to gain knowledge from the data in a reasonable time. The Top Down Induction...
Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly access...