Cross validation python

Cross 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.

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 validation

Source: scikit-learn.org

Similar codes

0 vote343 views1 answer
Sum values in django models and insert value in model field
Python Django
8 votes219 views2 answers
Python "is"
Python
0 vote264 views1 answer
Queryset to list python
Python
0 vote291 views1 answer
What is NoReverseMatch in django?
Python
0 vote293 views1 answer
WSGIPassAuthorization on
Python
0 vote238 views1 answer
FunÃ§Ã£o anonima python
Python
0 vote278 views1 answer
Python branchless programming
Python
0 vote263 views2 answers
Impute data by using groupby and transform
Python
5 votes262 views1 answer
Python pyautogui how to change the screenshot location
Python
3 votes249 views2 answers
Np argmin top n
Python