## How to check model's f1-score using cross validation in Python
def Snippet_133():
print()
print(format('How to check model\'s f1-score using cross validation in Python','*^82'))
import warnings
warnings.filterwarnings("ignore")
# load libraries
from sklearn.model_selection import cross_val_score
from sklearn.tree import DecisionTreeClassifier
from sklearn.datasets import make_classification
# Generate features matrix and target vector
X, y = make_classification(n_samples = 10000,
n_features = 3,
n_informative = 3,
n_redundant = 0,
n_classes = 2,
random_state = 42)
# Create Decision Tree model
dtree = DecisionTreeClassifier()
# Cross-validate model using accuracy
print(); print(cross_val_score(dtree, X, y, scoring="f1", cv = 7))
mean_score = cross_val_score(dtree, X, y, scoring="f1", cv = 7).mean()
std_score = cross_val_score(dtree, X, y, scoring="f1", cv = 7).std()
print(); print(mean_score)
print(); print(std_score)
Snippet_133()