APPLICATION OF SUPERVISED LEARNING
MACHINE LEARNINGHARD QUESTIONS
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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good fitting
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overfitting
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underfitting
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all of the above An underfit machine learning model is not a suitable model and will be obvious as it will have poor performance on the training data. Usually, a model that is underfit will have high training and high testing error
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Detailed explanation-1: -Underfitting refers to a model that can neither model the training data nor generalize to new data. An underfit machine learning model is not a suitable model and will be obvious as it will have poor performance on the training data.
Detailed explanation-2: -It will make inaccurate predictions when given new data, making the model useless even though it is able to make accurate predictions for the training data. This is called overfitting. The inverse is also true. Underfitting happens when a model has not been trained enough on the data.
Detailed explanation-3: -Increase the number of features in the dataset. Increase model complexity. Reduce noise in the data. Increase the duration of training the data. 20-Feb-2023