Question

Computer Science

Posted 7 months ago

K-nearest neighbors, Averaging (mean), Logistic regression

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Question 17
1 pts
Which of the following methods can be used for imputing (=filling in missing values)? Select all that apply.
K-nearest neighbours
Averaging (mean)
Classification
K-means clustering
Logistic regression
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Answer from Sia

Posted 7 months ago

The methods that can be used for imputing missing values are:

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K-nearest neighbours: This method imputes missing values based on the k-nearest neighbors, where k is a user-defined constant and the nearest neighbors are calculated using a distance metric

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Averaging (mean): This method replaces missing values with the mean value of the entire feature column, which is suitable for numerical data

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K-means clustering: Although not a direct imputation method, K-means can be used to impute missing values by assigning them to the nearest cluster centroid

Classification and Logistic regression are not typically used for imputing missing values as they are supervised learning methods used for predicting categorical outcomes, not for imputation.

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