APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Which are the correct statements?
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The cross entropy error function depicts the distance between two probability distributions
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The cross entropy error function is used to solve the classification problem.
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The mean square error function depicts the distance between two probability distributions
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The mean square error function is used to solve the regression problem
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Explanation:
Detailed explanation-1: -In regression, mean squares are used to determine whether terms in the model are significant. The term mean square is obtained by dividing the term sum of squares by the degrees of freedom. The mean square of the error (MSE) is obtained by dividing the sum of squares of the residual error by the degrees of freedom.
Detailed explanation-2: -RMSE is a square root of value gathered from the mean square error function. It helps us plot a difference between the estimate and actual value of a parameter of the model. Using RSME, we can easily measure the efficiency of the model.
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