Mean Squared Error
Advanced
Compute the mean squared error between aligned arrays of true targets and predictions.
Implement solve(y_true, y_pred).
Returns. Return a non-negative Python float, 0 for a perfect prediction.
Examples
Example 1
Input:
solve([3.0, -0.5, 2.0, 7.0], [2.5, 0.0, 2.0, 8.0])
Output:
0.375
Example 2
Input:
solve([1.0, 2.0, 3.0], [1.0, 2.0, 3.0])
Output:
0.0
Keywords
problemsetclassical-mlmetrics
Python
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