[USER (data scientist)]: Could you create a confusion matrix for the predictive model that uses credit history, employment, age, and credit amount to determine the probability of loan approval? Also, could you provide the accuracy of this model? Based on the results, I have a question: The model appears to have a fairly high accuracy of 70.5%. However, the confusion matrix suggests there may be an issue with false positives, as 56 instances were incorrectly identified. Could you clarify what these instances were incorrectly classified as? 

A. positives
B. negatives
C. None of above

[YOU (AI assistant)]: