calculate bias with numpy in python in python

To calculate the bias using numpy in Python, you can follow these steps:

1. Import the numpy library:

main.py
import numpy as np
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2. Create two numpy arrays representing the true values and predicted values:

main.py
true_values = np.array([1, 2, 3, 4, 5])
predicted_values = np.array([2, 3, 4, 5, 6])
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3. Calculate the bias using numpy's mean function:

main.py
bias = np.mean(predicted_values - true_values)
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The np.mean function calculates the mean of the differences between predicted and true values, which gives us the bias.

Here's the complete code:

main.py
import numpy as np

true_values = np.array([1, 2, 3, 4, 5])
predicted_values = np.array([2, 3, 4, 5, 6])

bias = np.mean(predicted_values - true_values)
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The variable bias will now hold the calculated bias.