APPLICATION OF SUPERVISED LEARNING
MACHINE LEARNING PIPELINE
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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A data scientist is trying to determine how a model is doing based on training evaluation. The train accuracy plateaus out at around 70% and the validation accuracy is 67%. How should the data scientist interpret these results?
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The model is underfit and needs more complexity
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The model is overfit and needs less complexity
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The model is generalizing well and isn’t overfit or underfit
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The model is overfit and underfit and needs more epochs
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Explanation:
Detailed explanation-1: -Explanation: Communication Building is not a part of data science process.
Detailed explanation-2: -Validation Dataset: The sample of data used to provide an unbiased evaluation of a model fit on the training dataset while tuning model hyperparameters.
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