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# 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])
```