Write a Python function precision that calculates the precision metric given two numpy arrays: y_true and y_pred. The y_true array contains the true binary labels, and the y_pred array contains the predicted binary labels. Precision is defined as the ratio of true positives to the sum of true positives and false positives.
Examples
Example 1:
Input:
import numpy as np
y_true = np.array([1, 0, 1, 1, 0, 1])
y_pred = np.array([1, 0, 1, 0, 0, 1])
result = precision(y_true, y_pred)
print(result)Output:
1.0Explanation: - True Positives (TP) = 3
- False Positives (FP) = 0
- Precision = TP / (TP + FP) = 3 / (3 + 0) = 1.0
Starter Code
import numpy as np
def precision(y_true, y_pred):
# Your code here
pass
Python3
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