VALIS is an effective and robust classification algorithm with a focus on understandability. Its name stems from Vote-ALlocating Immune System, as it evolves a population of artificial antibodies that can bind to the input data, and performs classification through a voting process. In the beginning of the training, VALIS generates a set of random candidate antibodies; at each iteration, it selects the most useful ones to produce new candidates, while the least, are discarded; the process is iterated until a user-defined stopping condition. The paradigm allows the user to get a visual insight of the learning dynamics, helping to supervise the process, pinpoint problems, and tweak feature engineering. VALIS is tested against nine state-of-the-art classification algorithms on six popular benchmark problems; results demonstrate that it is competitive with well-established black-box techniques, and superior in specific corner cases.
|Titolo:||VALIS: an evolutionary classification algorithm|
|Data di pubblicazione:||2018|
|Digital Object Identifier (DOI):||10.1007/s10710-018-9331-6|
|Appare nelle tipologie:||1.1 Articolo in rivista|