cross validation python
# SVC: support vector classifier (one of the "built-in" classifiers in scikit-learn)
# X, y: array-like representing input and target variables
# X.shape = (N, num_of_features)
# y.shape = (N, 1) in case of classification problem
from sklearn.model_selection import cross_val_score
clf = svm.SVC(kernel='linear', C=1, random_state=42)
scores = cross_val_score(clf, X, y, cv=5) # 5-fold cross validationcross validate does not have train_test_split
from sklearn.model_selection import train_test_splitcross validation
Cross-validation is a resampling procedure used to evaluate machine learning models on a limited data sample. The procedure has a single parameter called k that refers to the number of groups that a given data sample is to be split into. As such, the procedure is often called k-fold cross-validation.Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
