The accuracy score and confusion matrix are two essential tools for evaluating the performance of a logistic regression model. The accuracy score provides a general measure of how well the model is performing, while the confusion matrix provides more detailed information about the model’s ability to predict specific classes but in this I got a low accuracy that led me to move on to the next algorithm.