November 2023
Intermediate to advanced
576 pages
13h 30m
German
Content preview from Handbuch Data Science mit Python
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KAPITEL 47
Ausführlich: k-Means-Clustering
Im letzten Kapitel haben wir unüberwachte Machine-Learning-Modelle zur Dimensionsreduktion erkundet. Wir fahren nun mit einer weiteren Klasse solcher unüberwachten Modelle fort, nämlich mit Clustering-Algorithmen. Clustering-Algorithmen versuchen, anhand der Eigenschaften der Daten eine optimale Aufteilung der Datenpunkte in unterschiedliche Gruppen vorzunehmen (Zuordnung zu diskreten Labels).
In Scikit-Learn sind viele Clustering-Algorithmen verfügbar. Am einfachsten verständlich dürfte der k-Means-Algorithmus sein, der in sklearn.cluster.KMeans implementiert ist.
Wie gewohnt erfolgen zunächst die nötigen Importe:
In [1]: %matplotlib inline
import matplotlib.pyplot as plt
plt.style.use('seaborn-whitegrid') ...
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