Answer :
While testing data is used to evaluate the machine learning model's accuracy, training data is the subset of original data that is utilized to train the model.
What is the difference between test data and training data?
Data with all conceivable combinations of boundary values is used as test data to verify all boundary conditions. For instance, if a text box may accept values between 2 and 20, enter the lowest value of 2 and the maximum value of 20.
The diversity of training data types reflects the wide range of potential uses for machine learning algorithms. Text (words and numbers), photos, video, and audio can all be found in training datasets. Additionally, you may have access to them in a variety of formats, such as a spreadsheet, PDF, HTML, or JSON.
Training data is a subset of the original data that is used to train the machine learning model, whereas testing data is used to evaluate the model's correctness.
In comparison to the testing dataset, the training dataset is typically bigger.
Therefore, the correct answer is option A) Test data; Training data.
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