Page 147 - Ai_C10_Flipbook
P. 147

• Accuracy: If the model predicts, that the loan is approved or not approved, and it matches the reality, then that
                   means the model is accurate for that dataset.
                   Understanding both error and accuracy is crucial for effectively evaluating and improving AI models.

                                                             Prediction
                     Approval of Loan          AI Model                      Loan Approved
                                                                                                            Approved
                                                                                    –
                                                               Actual
                                                                             Loan Approved

                 Understanding both error and accuracy is crucial for effectively evaluating and improving AI models. From the
                 above example we can say,
                    • The focus is to maximise the accuracy in the performance of the model and minimise the error.
                    • In real life scenarios, the accuracy is dependent on the data, if the dataset is not realistic, the best models
                   may make mistakes. For example, in approval of loan, a model with slightly lower accuracy but the focus is on
                   avoiding incorrectly identifying a right applicant may be preferred by the banks.
                    • Selection of the model with the balance of accuracy and error depends upon the task and its requirements by
                   the model


                              Task                                                          21 st  Century   #Information Literacy
                                                                                                Skills
                                                                                                    #Critical Thinking

                   Find the accuracy of the AI model mathematically.
                   Calculate the accuracy of AI model which predicts the salary of employees:

                      • Using the given formulae complete the given table:
                       Error Absolute = ABS(Actual Value -Predicted Value)
                       Error Rate        =  (Error/Actual value)
                       Accuracy           = (1-Error Rate)
                       Accuracy%       = (Accuracy*100)%

                       Predicted Salary   Actual Salary  Error Absolute   Error Rate      Accuracy        Accuracy%
                       47,000             45,000         2,000           2,000/45,000  1-0.044=0.956   0.956*100=95.6%
                                                                         =0.044
                       56,000             56,500         500             500/56,500    1-0.008=0.992   0.992*100=99.2%
                                                                         =0.008

                       45,000             45,500         500
                       38,000             37,000         1,000
                       65,000             67,000         2000
                      • Accuracy of the AI model is the mean accuracy of all five samples.
                                                                        (Sum of Accuracy%)
                                               Accuracy of the AI model =
                                                                      Total number of samples

                   Complete the above table and find the accuracy of the AI model.








                                                                                           Evaluating Models    145
   142   143   144   145   146   147   148   149   150   151   152