Page 251 - AI Ver 3.0 class 10_Flipbook
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Assertion and Reasoning questions.
                    Direction: Questions 2-4, consist of two statements – Assertion (A) and Reasoning (R). Answer these questions by selecting
                    the appropriate option given below:

                       a. Both A and R are correct, and R is the correct explanation of A.
                       b. Both A and R are correct, but R is NOT the correct explanation of A.
                       c. A is correct, but R is incorrect.
                       d. A is incorrect, but R is correct.

                    2.  Assertion (A): A model with high accuracy always performs well on all types of classification problems.
                       Reasoning(R): Accuracy is a reliable metric for evaluating model  performance in all scenarios.
                    3.  Assertion (A): Bias in training  data  can lead  to unfair predictions in AI models.
                       Reasoning (R): If  the training  dataset  lacks diversity, the model  may  learn and reinforce existing biases.
                    4.  Assertion (A): Accuracy is an evaluation metric that allows you to measure the total number of predictions a model
                       gets right.
                       Reasoning (R): The accuracy of the model and performance of the model is directly proportional, and hence better the
                       performance of the model, the more accurate are the predictions.                   [CBSE Handbook]

                                    In Life                                                 21 st  Century   #Communication
                                                                                                    #Initiative
                                                                                                Skills

                     How can evaluation techniques be applied to assess the effectiveness of educational programs or courses? Share
                     your examples of specific methods used to gather data and measure learning outcomes with the class.



                                Deep Thinking
                                                                                             21 st  Century   #Critical Thinking
                                                                                                 Skills
                     An educational institution is implementing a new online learning platform to enhance student engagement. The
                     administrators want to evaluate its effectiveness and identify areas for improvement. What quantitative methods
                     could be employed to measure student participation and learning outcomes on the new platform? Share your
                     thoughts with the class.


                                                                                          21 st  Century   #Technology Literacy
                                                                                              Skills
                                 Lab




                          1.  Explore the internet to find some scenarios related to natural disasters. Take any one out of them and
                             make prediction-reality comparison. Draw a confusion matrix for it to show prediction results.

                          2.  For the scenario in the above question, make evaluation through its parameters_ Accuracy, Precision and
                             Recall.
                          3.  Calculate the following measures for the given confusion matrix - Accuracy, Precision, Recall and F1 Score.

                                  Confusion Matrix        True Positive            True Negative
                                 Predictive Positive           100                      45
                                 Predicted Negative            65                      320




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