pyml.utils.accuracy.RegressionAccuracy#

class RegressionAccuracy[source]#

Bases: _Accuracy

Subclass of _Accuracy tailored for regression models.

Calculates accuracy based on precision and compares predictions to ground truth.

Variables:: precision (float) – Precision value used for regression accuracy calculation.

Initialize RegressionAccuracy instance.

Methods

`__init__`	Initialize RegressionAccuracy instance.
`calculate`	Calculate accuracy based on predictions and ground truth values.
`calculate_accumulated`	Calculate accumulated accuracy.
`compare`	Compare predictions to ground truth values for regression accuracy.
`init`	Initialize regression accuracy calculation parameters.
`reset`	Reset variables for accumulated accuracy.

calculate(predictions, y)#

Calculate accuracy based on predictions and ground truth values.

Return type:

float

Parameters:

Returns:

Calculated accuracy.

Return type:

float

calculate_accumulated()#

Calculate accumulated accuracy.

compare(predictions, y)[source]#

Compare predictions to ground truth values for regression accuracy.

Return type:

ndarray

Parameters:

Returns:

Array of comparison results.

Return type:

numpy.ndarray

init(y, reinit=False)[source]#

Initialize regression accuracy calculation parameters.

Return type:

None

Parameters:

y (numpy.ndarray) – Ground truth values.
reinit (bool, optional) – Reinitialize precision if True, by default False

reset()#

Reset variables for accumulated accuracy.