COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Error that results from inaccurate assumptions in model training
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Error that occurs when the model is too sensitive to the training data
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Either A or B
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None of the above
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Detailed explanation-1: -What is bias in machine learning? Bias is a phenomenon that skews the result of an algorithm in favor or against an idea. Bias is considered a systematic error that occurs in the machine learning model itself due to incorrect assumptions in the ML process.
Detailed explanation-2: -The bias error is an error from erroneous assumptions in the learning algorithm. High bias can cause an algorithm to miss the relevant relations between features and target outputs (underfitting). The variance is an error from sensitivity to small fluctuations in the training set.
Detailed explanation-3: -What Is Bias? Also called “error due to squared bias open in new, ” bias is the amount that a model’s prediction differs from the target value, compared to the training data. Bias error results from simplifying the assumptions used in a model so the target functions are easier to approximate.
Detailed explanation-4: -Machine learning bias, also sometimes called algorithm bias or AI bias, is a phenomenon that occurs when an algorithm produces results that are systemically prejudiced due to erroneous assumptions in the machine learning process.