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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
Evaluating Models 227

