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0.72 × 0.63
                                     2 ×       = 0.67
                                    0.72 + 0.63
                        A good F1 score means there are low false positive and low false negative values. In such a case, the AI model is
                        correctly identifying the real threats and giving less false alarms. However, the above model has already predicted
                        325 True Negatives which is quite high and F1 score is also not very good. Hence, the AI model needs to be
                        retrained.
              C.   Competency-based/Application-based questions:

                     The following question consist of two statements: Assertion (A) and Reason (R).
                   Assertion (A): Binary Classification represents those classification tasks that have more than two class labels.
                   Reason (R): Multiclass classification does not have the concept of normal and abnormal classes.
                   Answer the question selecting the appropriate option given below:
                   a.  Both A and R are true and R is the correct explanation of A
                   b.  Both A and R are true and R is not the correct explanation of A
                   c.  A is true but R is false
                   d.  A is false but R is true
              Ans.  d



                                                     Unsolved Questions


                                                SECTION A (Objective Type Questions)
                        uiz

              A.   Tick ( ) the correct option.
                   1.                 classification tasks involve 2 labels—normal and abnormal.
                        a.  General                                    b.  Binary
                        c.  Multiclass                                 d.  All of these

                   2.   A false positive, in medical testing, is actually an   .
                        a.  prediction                                 b.  true value
                        c.  error                                      d.  None of these

                   3.                 clustering builds a tree of clusters.
                        a.  Centroid-based                             b.  Distribution-based
                        c.  Density-based                              d.  Hierarchical

                   4.                 is rather used for the discovery of knowledge rather than for prediction.
                        a.  Regression                                 b.  Classification
                        c.  Clustering                                 d.  Decision Trees
                   5.   John is grouping animals as herbivores, carnivores and omnivores. What is this technique called in machine learning?
                        a.  Regression                                 b.  Classification

                        c.  Clustering                                 d.  Decision Trees
              B.   Fill in the blanks.
                   1.                 based clustering arranges the data into non-hierarchical clusters.
                   2.   Two applications of logistic regression are       and               .
                   3.   A               evaluates the performance of a classification model.


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