pyml.utils.accuracy#

This module contains classes for calculating accuracy metrics in machine learning tasks.

It provides different accuracy calculation methods for classification and regression models.

Classes#

_Accuracy (ABC):

Abstract base class defining the structure for accuracy metrics. Subclasses must implement methods for initialization and comparison. Also, methods are provided for calculating accuracy and handling accumulated accuracy.

MultiClassAccuracy:

A subclass of _Accuracy specifically for multi-class classification models. Implements methods to compare predictions and ground truth values for accuracy calculation.

BinaryClassAccuracy:

A subclass of _Accuracy designed for binary classification models. Compares predictions and ground truth values to compute accuracy.

RegressionAccuracy:

A subclass of _Accuracy tailored for regression models. Calculates accuracy based on precision and compares predictions to ground truth.

Classes

BinaryClassAccuracy

Subclass of _Accuracy designed for binary classification models.

MultiClassAccuracy

Subclass of _Accuracy specifically for multi-class classification models.

RegressionAccuracy

Subclass of _Accuracy tailored for regression models.