LEAD SCORE ERROR
Beginner
Difficulty: Easy Tags: Loss Functions
Story
A lead-scoring regressor is graded against actual conversion likelihood using the most standard regression loss there is, but it has to match the framework reference exactly before it ships into the training loop.
The Math
MSE = (1/n) * sum_i (y_i - yhat_i)^2
Input Format
n
y_1 yhat_1
...
y_n yhat_n
Output Format
Scalar MSE, 6 decimals.
Constraints
1 <= n <= 10^6- Time limit: 1.0 second.
Example
Input
4
3 2.5
5 5
2.5 4
7 8
Output
0.875000
Keywords
loss-functions
Python
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