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Question $13$ options:

This fit command causes a number of model$-$dependent internal computations to take place, and the results of these computations are stored in model$-$specific attributes that the user can explore via Python statements.

Once the model is trained within your Python program, the main task of supervised machine learning is to evaluate it based on what it says about existing $($test$)$ data that was part of the training set, using the predict method.

The input variable y for model training is in the correct form of $[$n$\_$samples$]$ array $,$ while the output variable x is a matrix of size $[$n$\_$samples, n$\_$features$]$