July 2017
Intermediate to advanced
378 pages
10h 44m
German
Content preview from Einführung in Machine Learning mit PythonBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Receiver Operating Characteristic (ROC) und AUC
Es gibt ein weiteres, verbreitetes Werkzeug zum Analysieren des Verhaltens von Klassifikatoren bei verschiedenen Schwellenwerten: die Receiver-Operating-Characteristic-, kurz ROC-Kurve. Ähnlich zur Relevanz-Sensitivitäst-Kurve betrachtet die ROC-Kurve alle möglichen Schwellenwerte eines gegebenen Klassifikators, aber anstatt Relevanz und Sensitivität zu berechnen, zeigt sie die Falsch-positiv-Rate (FPR) über der Richtig-positiv-Rate (RPR). Die Richtig-positiv-Rate ist wie oben erwähnt einfach ein anderer Name für die Sensitivität, während die Falschpositiv-Rate der Anteil an falsch positiven an allen negativen Datenpunkten ist:
Die ROC-Kurve lässt sich mit der Funktion roc_curve berechnen (siehe ...
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