A theoretical and experimental analysis of linear combiners for multiple classifier systems

By Giorgio Fumera, Fabio Roli. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005

331 citations recorded by the source corpus.

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Learn$^{++}$ .NC: Combining Ensemble of Classifiers With Dynamically Weighted Consult-and-Vote for Efficient Incremental Learning of New Classes (2009, unknown): “algebraic combinations of posterior probabilities [43], [51], Dempster–Shafer combination [52], decision templates [53], or meta decision trees [54].”
A survey of multiple classifier systems as hybrid systems (2014, methodology): “Some analytical properties and experimental evaluations of aggregating methods were presented in [10,31,143,144].”
Ensemble based systems in decision making (2006, background): “Does the no-free-lunch theorem hold for combination rules as well? Many studies have been conducted to answer this question, including [18], [27], [28], [31], [36], [37], [42], [71], [72], among others.”