Question 6Which of the following statements about datasets used in Machine Learning is NOT true?1 pointTesting data is data the model has never seen before and is used to evaluate how good the model isTraining subset is the data used to train the algorithm Training data is used to fine-tune algorithm’s parameters and evaluate how good the model isValidation data subset is used to validate results and fine-tune the algorithm's parameters
Question
Question 6Which of the following statements about datasets used in Machine Learning is NOT true?1 pointTesting data is data the model has never seen before and is used to evaluate how good the model isTraining subset is the data used to train the algorithm Training data is used to fine-tune algorithm’s parameters and evaluate how good the model isValidation data subset is used to validate results and fine-tune the algorithm's parameters
Solution
The statement that is NOT true about datasets used in Machine Learning is: "Training data is used to fine-tune algorithm’s parameters and evaluate how good the model is".
Explanation:
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Testing data: This is correct. Testing data is indeed data that the model has never seen before and is used to evaluate the performance of the model.
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Training subset: This is also correct. The training subset is the data used to train the algorithm.
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Training data: This statement is incorrect. Training data is used to train the model, not to fine-tune the algorithm's parameters or evaluate how good the model is. The model's performance is evaluated using the validation and testing data.
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Validation data subset: This is correct. The validation data subset is used to validate the results and fine-tune the algorithm's parameters. It provides a 'unbiased' evaluation of a model fit on the training dataset while tuning the model's hyperparameters (e.g. the number of hidden units in a neural network).
Similar Questions
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