objectif

SVM kernel RBF avec sorties probabilistes.

code minimal

from sklearn.svm import SVC
from sklearn.datasets import load_iris
X, y = load_iris(return_X_y=True)
clf = SVC(kernel="rbf", probability=True, gamma="scale").fit(X, y)
print(hasattr(clf, "predict_proba"))

utilisation

from sklearn.svm import LinearSVC
print(hasattr(LinearSVC(), "fit"))

variante(s) utile(s)

from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import make_pipeline
print(hasattr(make_pipeline(StandardScaler(), SVC()), "fit"))

notes

• SVC coûteux en O(n^2) mémoire; échantillonner si nécessaire.