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- """
- Contains all metrics used for model results comparisons
- """
- # main imports
- import numpy as np
- def coefficient_of_determination(y, predicted):
- """Returns the coefficient of determination between `y` and `y_predicted` values
- Args:
- y: array of reference values
- predicted: array of predicted values
- Returns:
- coefficient of determination
- Example:
- >>> from ipfml import metrics
- >>> import numpy as np
- >>> y = np.arange(10)
- >>> predicted = np.arange(10) * 1.05
- >>> coeff = metrics.coefficient_of_determination(y, predicted)
- >>> int(coeff)
- 1
- """
- y = np.asarray(y)
- predicted = np.asarray(predicted)
- y_mean = y.mean()
- numerator_sum = 0
- denominator_sum = 0
- for id_val, val in enumerate(y):
- numerator_sum += (predicted[id_val] - y_mean) * (
- predicted[id_val] - y_mean)
- denominator_sum += (val - y_mean) * (val - y_mean)
- return numerator_sum / denominator_sum
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