Question

Which of the following is NOT a commonly used Loss Function in Machine Learning?

Cross Entropy
Mean Absolute
Mean Square
Sinusoidal​

Answer 1

Answer:

Sinusoidal​

Explanation:

Answer 2

Option D) Sinusoidal​

Sinusoidal​ is NOT a commonly used Loss Function in Machine Learning.

• The loss function can be used to assess how effectively your machine learning algorithm predicts the highlighted data set. To put it another way, loss functions are a gauge of how well your model can predict the desired result.

• There are numerous popular loss functions to pick from, including the cross-entropy loss, mean-squared error, huber loss, and hinge loss, to mention a few.
• For a given random variable or series of events, cross-entropy is a measurement of the difference between two probability distributions. Information measures the amount of bits needed to encode and transmit an event, as you may recall.
• In order to change the model weights during training, cross-entropy loss is used. The goal is to reduce loss; hence, the better the model, the smaller the loss. A cross-entropy loss of zero indicates a flawless model.

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