COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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True
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False
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Either A or B
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None of the above
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Detailed explanation-1: -Grid search is a method of parameter adjustment. When dealing with actual problems, when should machine learning be used? The data distribution itself changes over time and requires continuous re-adaptation of the program, such as predicting the trend of merchandise sales.
Detailed explanation-2: -Grid search is a method for performing hyper-parameter optimisation, that is, with a given model (e.g. a CNN) and test dataset, it is a method for finding the optimal combination of hyper-parameters (an example of a hyper-parameter is the learning rate of the optimiser).
Detailed explanation-3: -Grid search is a process that searches exhaustively through a manually specified subset of the hyperparameter space of the targeted algorithm. Random search, on the other hand, selects a value for each hyperparameter independently using a probability distribution.
Detailed explanation-4: -One method is to try out different values and then pick the value that gives the best score. This technique is known as a grid search. If we had to select the values for two or more parameters, we would evaluate all combinations of the sets of values thus forming a grid of values.