Question

2. (1)
1 point possible (graded, results hidden)
If we again use the linear perceptron algorithm to train the classifier, what will happen?

Note: In the choices below ,“converge" means given a certain input, the algorithm will terminate with a fixed output within finite steps (assume is very large: the output of the algorithm will not change as we increase ). Otherwise we say the algorithm diverges (even for an extremely large , the output of the algorithm will change as we increase further).

Answer 1

Without additional information about the dataset and its separability, it is impossible to say definitively what will happen when using the linear perceptron algorithm to train the classifier. The algorithm may converge and successfully classify the data, or it may not converge and fail to find a linear separation.