November 2019
Intermediate to advanced
320 pages
13h 35m
French
Content preview from Machine Learning avec Scikit-Learn
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2.4 Découvrir et visualiser les données pour mieux les comprendre
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2.4.2 Recherche de corrélations
Étant donné que le jeu de données est de taille raisonnable, vous pouvez aisément
calculer le coefcient de corrélation (appelé également r de Pearson) entre chaque
couple de variables en utilisant la méthode corr() :
corr_matrix = housing.corr()
Regardons maintenant quelle est la corrélation entre chacune des variables et la
valeur médiane des habitations (median_house_value) :
>>> corr_matrix["median_house_value"].sort_values(ascending=False)
median_house_value 1.000000
median_income 0.687170 ...
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