matrics_calculator.r2

Functions

r2(y_pred, y_true)

Calculates r-squared using linear regression.

Module Contents

matrics_calculator.r2.r2(y_pred, y_true)[source]

Calculates r-squared using linear regression.

Computes the r-squared value (coefficient of determination) using the provided y_pred list and y_true list.

Parameters:

y_pred (list) – y_pred values to be used in calculating r-sqaured value.
y_true (list) – y_true values to be used in calculating r-sqaured value.

Returns:

r-sqaured value which is <= 1. 1 is the best score and a score below 0 is worse than using the mean of the target as predictions.

Return type:

float

Examples

>>> data = {
>>> 'math_test': [80, 85, 90, 95],
>>> 'science_test': [78, 82, 88, 92],
>>> 'final_grade': [84, 87, 91, 94],
>>> 'absences': [3, 0, 1, 30]
>>> }
>>> r2(data['math_test'],data['final_grade'])
0.997
>>> r2(data['math_test'],data['absences'])
0.541