Collaborative data stream mining in ubiquitous environments using dynamic classifier selection

 The expansionary monetary policy measures have had a negative impact on net interest margins both via the reduction in interest rates and –less powerfully- the flattening of the

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The aim of this study is to analyse the factors related to the use of addictive substances in adolescence using association rules, descriptive tools included in Data Mining.. Thus,

The programming language most widely used in data mining is Python, primarily because of its ver- satility and the number of libraries that are available for data processing,

The incomplete information might be due to the size of interaction data, since 300 instances (24 students) was not sufficient for applying data mining methods in

In this paper we present an enhancement on the use of cellular automata as a technique for the classification in data mining with higher or the same performance and more

(hundreds of kHz). Resolution problems are directly related to the resulting accuracy of the computation, as it was seen in [18], so 32-bit floating point may not be appropriate

The way they aggregate data from the incoming stream of records is to maintain a hash table with different keys, which are a specific field of the record, contain- ing a set of