July 2020
Intermediate to advanced
852 pages
25h 44m
German
book
Praxiseinstieg Machine Learning mit Scikit-Learn, Keras und TensorFlow, 2nd Edition
by Aurélien Géron
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KAPITEL 6
Entscheidungsbäume
Wie SVMs sind auch Entscheidungsbäume sehr flexible Machine-Learning-Algorithmen, die sich sowohl für Klassifikations- als auch für Regressionsaufgaben eignen. Sogar Aufgaben mit multiplen Ausgaben lassen sich mit ihnen lösen. Es sind sehr mächtige Algorithmen, mit denen sich komplexe Datensätze fitten lassen. Beispielsweise haben Sie in Kapitel 2 ein Modell mit dem DecisionTreeRegressor trainiert und an den Datensatz zu kalifornischen Immobilien perfekt angepasst (genauer gesagt, overfittet).
Entscheidungsbäume sind außerdem die funktionelle Komponente von Random Forests (siehe Kapitel 7), die zu den mächtigsten heute verfügbaren Machine-Learning-Algorithmen gehören.
In diesem Kapitel werden wir besprechen, wie sich ...
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