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- W2904340577 abstract "Taking decisions is an inseparable part of our everyday life. Decisions are either taken single-handedly or collectively. There are many methods of collective decision making. These methods refer to various bodies known in real life such as parliaments, supervisory boards, councils, juries, families, and to distributed systems such as blockchains. Such organisation of collaboration on which a decision process is based, makes it possible to eliminate effects of mistakes, insufficient knowledge or even an intentional sabotage attempted by a single participant. The method of determining the final decision is selected taking into account specific reasons and goals. Without going into details one type of voting requires a relative majority while other ones an absolute majority or a simple majority. In machine learning, there are two main groups of meta-algorithms which organise voting, and primarily the learning process in an ensemble of decision systems. They are the boosting and bagging methods. The most popular algorithm of the boosting kind is the Ada-Boost." @default.
- W2904340577 created "2018-12-22" @default.
- W2904340577 creator A5080246635 @default.
- W2904340577 date "2018-12-18" @default.
- W2904340577 modified "2023-09-26" @default.
- W2904340577 title "Ensembles of Rough Set–Based Classifiers" @default.
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- W2904340577 doi "https://doi.org/10.1007/978-3-030-03895-3_7" @default.
- W2904340577 hasPublicationYear "2018" @default.
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