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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Which of the following will be true about k in K-Nearest Neighbor in terms of Bias?
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When you decrease the k the bias will be increases
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When you increase the k the bias will be increases
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Both (A) and (B)
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None of the Above When you increase the k the bias will be increases
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Explanation:
Detailed explanation-1: -4) Which of the following option is true about k-NN algorithm? We can also use k-NN for regression problems. In this case the prediction can be based on the mean or the median of the k-most similar instances.
Detailed explanation-2: -The statement that is true about the effect of the number of neighbors parameter k is: 1. For small values of k (e.g. k = 1), the classifier will tend to be much more sensitive to noise, mislabeled data, and other sources of variation for individual data points.
Detailed explanation-3: -K should be the square root of n (number of data points in the training dataset). K should be chosen as the odd so that there are no ties.
There is 1 question to complete.