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












                         Evaluation Metrics for Classification



                 Classification is a type of supervised learning in machine learning where the goal is to predict the categorical label
                 or class of a given input based on historical data. In classification tasks, the model is trained on a labelled dataset,
                 where a specific type of class label is the result to be predicted from the given input field of data. The model learns
                 to map inputs to the correct category during the training phase.

                 What is Classification?

                 Classification is the task of “classifying things” into sub-categories. Classification is part of supervised machine
                 learning in which we put labelled data for training.
                 For  example,  You  and  your  friends  go  to  a  restaurant,  where  pure  vegetarians  sit  together  at  one  table  and
                 non-vegetarians sit together at another table, to ensure that there is no confusion while serving food.


















                 So basically, you are classifying your friends into two categories:
                    • Pure vegetarians
                    • Non-vegetarians


                                      CLASSIFICATION IN MACHINE LEARNING










                                                                                           Vegetarian
                                                                                           Non-vegetarian
                                                                                           Eggetarian
                                                                                           Vegan
                                            4 Classes                 2 Classes



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