Establish how good the predictions were, this is done by a confusion matrix. You take the test data and compare it to the prediction. You will need to make a 2x2 with true positives, true negatives, false positives, and false negatives. Find all the metrics of performance that may be relevant and evaluate your predictions. Please discuss your findings

RStudio Edit Code View Plots Session Build Debug Profile Tools Help Environment History Cometions Tutorin 1 1brary (@1071) credit_training - read. cav( "credit_training. cs") Data Ocisf List of $ credit_ceste-read. cav["credit_test. cav") O credit_test 309 obs. of 20 variables history_cesc library (e1071) MACHINE LEARNING ABOX Mer 20, 2082, B credit_training cable (predictions) predictions fully repaid 18 21 fully repaid this back repaid > tablechistory_test) history_ceut critical delayed fully repaid 22 13 fully repaid this bank repaid 19