True negative

True negative

Das Ergebnis eines statistischen Tests ist richtig negativ, wenn korrekt angezeigt wird, dass das gesuchte Ergebnis nicht gefunden ist. Da jeder Algorithmus, der etwas nachweisen soll, eine Tendenz hat Falschalarme zu produzieren wird dies grundsätzlich nicht in allen Fällen zutreffen. Es treten Fehler 1. und 2. Art auf.

Beispiel

Eine Krankheit hat den Grundanteil 100 von 10000, das heißt im Schnitt sind 100 von 10000 Personen erkrankt. Ein medizinischer Test soll das Vorhandensein der Krankheit feststellen (positives Testergebnis), kommt aber in einem Prozent der Fälle zum falschen Schluss. Diese Situation kann mittels des folgenden Entscheidungsbaums dargestellt werden:

         10000
           ^
         /   \
        /     \
krank 100     9900 gesund
      ^         ^
     / \       / \
    /   \     /   \
   99    1   99    9801
   +      -   +    -

Der richtig negative Test ist hier rot hervorgehoben. Es bedeutet, dass durch die Fehlerrate von 1% 9801 der 9900 gesunden Testpersonen tatsächlich als gesund erkannt werden.

Siehe auch

Beurteilung eines Klassifikators


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