In the problem of probability forecasting the learner’s goal is to output, given a training set and a new object, a suitable probability measure on the possible values of the ne...
In many application scenarios the database is changing quite rapidly. Because the management of such data is rather expensive and cumbersome, many applications like data warehouse...
We use game theory to analyze meta-learning algorithms. The objective of meta-learning is to determine which algorithm to apply on a given task. This is an instance of a more gene...
Abstract. In electronic commerce, traded digital objects are likely associated with several numerical values as well as their prices. These values may change unpredictably over tim...
The Local Outlier Factor (LOF) is a very powerful anomaly detection method available in machine learning and classification. The algorithm defines the notion of local outlier in...