Model Accuracy

Model accuracy measures the proportion of correct predictions made by a machine learning model. The accuracy score is calculated as the ratio of true positives to total instances tested A high model accuracy indicates that the model is reliable and effective in making predictions Accuracy is one of the most common metrics used to evaluate the performance of machine learning models Model accuracy can be affected by factors like dataset quality, feature engineering, and regularization techniques