how-to-use-k-fold-cross-validation.md

How to use K fold cross validation

from sklearn import datasets, linear_model
from sklearn.model_selection import cross_val_score
diabetes = datasets.load_diabetes()
X = diabetes.data[:150]
y = diabetes.target[:150]
lasso = linear_model.Lasso()

cvs = cross_val_score(lasso, X, y, cv=3)

• from sklearn import - import module from lib:scikit-learn
• datasets.load_diabetes - loads sample diabetes database
• linear_model.Lasso - creates Lasso model
• cross_val_score( - evaluates a score by cross-validation
• lasso - model to use for cross-validation
• cv=3 - number of folds (3 in our case) to use

group: cross-validate

Example:

from sklearn import datasets, linear_model
from sklearn.model_selection import cross_val_score
diabetes = datasets.load_diabetes()
X = diabetes.data[:150]
y = diabetes.target[:150]
lasso = linear_model.Lasso()

cvs = cross_val_score(lasso, X, y, cv=3)
print(cvs)

[0.3315057  0.08022103 0.03531816]