v Precision - Machine Learning

Precision

Preliminaries

# Load libraries
from sklearn.model_selection import cross_val_score
from sklearn.linear_model import LogisticRegression
from sklearn.datasets import make_classification

Generate Features And Target Data

# 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 = 1)

Create Logistic Regression

# Create logistic regression
logit = LogisticRegression()

Cross-Validate Model Using Precision

# Cross-validate model using precision
cross_val_score(logit, X, y, scoring="precision")
array([ 0.95252404,  0.96583282,  0.95558223])