"sklearn support vector machine" Code Answer's
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scikit learn svm
Determined Dotterel
on Jul 29, 2020
from sklearn import svm
X = [[0, 0], [1, 1]]
y = [0, 1]
clf = svm.SVC()
clf.fit(X, y)
clf.predict([[2., 2.]])Source: scikit-learn.org
sklearn support vector machine
Famous Fox
on May 25, 2021
from sklearn import svm
X = [[0, 0], [2, 2]]
y = [0.5, 2.5]
regr = svm.SVR()
regr.fit(X, y)
regr.predict([[1, 1]])All those coders who are working on the Python based application and are stuck on sklearn support vector machine can get a collection of related answers to their query. Programmers need to enter their query on sklearn support vector machine related to Python code and they'll get their ambiguities clear immediately. On our webpage, there are tutorials about sklearn support vector machine for the programmers working on Python code while coding their module. Coders are also allowed to rectify already present answers of sklearn support vector machine while working on the Python language code. Developers can add up suggestions if they deem fit any other answer relating to "sklearn support vector machine". Visit this developer's friendly online web community, CodeProZone, and get your queries like sklearn support vector machine resolved professionally and stay updated to the latest Python updates.
