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

Question

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

Accepted Answer

⚹ The methods that can be used for imputing missing values are: ⚹ ‖ ▪ ⋮ 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. ‖ ‖ ▪ ⋮ Averaging (mean): This method replaces missing values with the mean value of the entire feature column, which is suitable for numerical data. ‖ ‖ ▪ ⋮ 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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