What is the precision score in machine learning?

What is the precision score in machine learning?

The precision score is a metric that measures the accuracy of positive predictions in a classification model.

How is precision calculated?

Precision is calculated as the ratio of true positive predictions to the total number of positive predictions: Precision = TP / (TP + FP).

Can you give me an example of how to calculate it in Python?

Sure! You can use the precision_score function from the sklearn.metrics module. Here's a simple example:

from sklearn.metrics import precision_score

# True labels
y_true = [1, 0, 1, 1, 0, 1]
# Predicted labels
y_pred = [1, 0, 1, 0, 0, 1]

precision = precision_score(y_true, y_pred)
print('Precision:', precision)

What does a high precision score indicate?

A high precision score indicates that a large proportion of positive predictions made by the model are actually correct.