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Verbesserung von Klassifikationsverfahren

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Springer Nature
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9783658114763
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Dominik Koch weist in seinen Studien nach, dass es mit Hilfe der k-Nchsten-Nachbarn mglich ist, die Ergebnisse anderer Klassifikationsverfahren so zu verbessern, dass sie wieder eine Konkurrenz zu dem meist dominierenden Random Forest darstellen. Das von Fix und Hodges entwickelte k-NchsteNachbarn-Verfahren ist eines der simpelsten und zugleich intuitivsten Klassifikationsverfahren. Nichtsdestotrotz ist es in den meisten Fllen in der Lage, ziemlich gute Klassifikationsergebnisse zu liefern. Diesen Informationsgehalt der k-Nchsten-Nachbarn kann man sich zu Nutze machen, um bereits etablierte Verfahren zu verbessern. In diesem Buch werden die Auswirkungen der k-Nchsten-Nachbarn auf den Boosting-Ansatz, Lasso und Random Forest in Bezug auf binre Klassifikationsprobleme behandelt.

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