Question

47.
_approach is to make a reasonable guess for the missing value of certain fields.
A. Heuristic-based imputation
B. Imputation by nearest neighbor
C. Random value imputation
I
D. Imputation by interpolation

Answer 1

Answer:

B.Imputation by nearest neighbor

Explanation:

k-Nearest Neighbor Imputation

A dataset may have missing values.

These are rows of data where one or more values or columns in that row are not present. The values may be missing completely or they may be marked with a special character or value, such as a question mark “?“.

Values could be missing for many reasons, often specific to the problem domain, and might include reasons such as corrupt measurements or unavailability.

Most machine learning algorithms require numeric input values, and a value to be present for each row and column in a dataset. As such, missing values can cause problems for machine learning algorithms.

It is common to identify missing values in a dataset and replace them with a numeric value. This is called data imputing, or missing data imputation.