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

1 vote349 views1 answer
How to get maximum value of number in python
Python
12 votes360 views4 answers
Merge three dataframes pandas based on column
Python
0 vote395 views1 answer
How to convert a matrix string back to a matrix python
Python
0 vote344 views1 answer
How to count to 1billion in python
Python
1 vote367 views2 answers
Selenium text value is empty in flask returns
Python
2 votes350 views1 answer
How to load ui file in pyqt5
Python
0 vote354 views1 answer
Django is .get lazy
Python
20 votes364 views6 answers
Random Number Generator
Python
0 vote360 views1 answer
Windows error message python
Python
5 votes356 views2 answers
Append string variable with integer python
Python