Machine Learning

                                                                                                    UNIT-II                                                                                           CLASSIFICATION Long Answer Questions   1.      Apply a Binary Classifier for a given dataset and evaluate its performances using Accuracy, Precision, Recall, F1 Score, Precision/Recall Trade-off.   Not 5 5 Not 5 53057 1522 5 1325 4096   2.      Explain kNN Classifier Algorithm with an example. 3.      How can you be measuring accuracy using cross validation? Explain. 4.      Predict the class label for new instance x1=6, x2=8 for the following dataset using kNN Classifier. Explain kNN Algorithm. X1 X2 Class Label 4 3 F 6 7 P 7 8 P 5

  1.      By default, SGD classifier follows this strategy for multi-class classification: Top of Form A)    OvO strategy B)     OvA strategy C)     Both D)    None Ans: B 2.      SGD Classifiers and Linear Classifiers are strictly A)    Binary Classifier B)     Multiclass classifier C)     Both D)    None      Ans: A 3.      The greater the value for ROC AUC, better the model: Top of Form A)    True B)     False Bottom of Form Ans: A 4.      The maximum value of the ROC AUC is Top of Form A)     0.8 B)      0.9  C)      1 D)     0.7 Bottom of Form Ans: C 5.      Recall can be increased by increasing the decision threshold. True or False Top of Form ? A)     False B)      True Ans: A 6.      Precision can be increased by increasing the decision threshold. True or False? A)    True B)     False Ans: A   7.      Which of these is a good measure to decide which threshold to use? A)    Top of Form A)    Confusion m