accuracy

in the context of binary classification, accuracy is defined as the proportion of true results (both true positives and true negatives) to the total number of cases examined (the sum of true positive, true negative, false positive and false negative). It can be understood as a measure of the proximity of measurement results to the true value. Accuracy is a metric used in the context of classification tasks to evaluate the proportion of correctly predicted instances among the total instances. Key Points: Use Case: Classification performance evaluation. Metric: Measures the proportion of correct predictions. Interpretation: Higher values indicate better classification performance.