Question

Name the another possible method to handle the data ​

Answer 1

Step-by-step explanation:

Missing Completely At Random (MCAR): When missing values are randomly distributed across all observations, then we consider the data to be missing completely at random. A quick check for this is to compare two parts of data – one with missing observations and the other without missing observations. On a t-test, if we do not find any difference in means between the two samples of data, we can assume the data to be MCAR.

please mark brainlist

Answer 2

Answer:

Random forest is a non-parametric imputation method applicable to various variable types that works well with both data missing at random and not missing at random. Random forest uses multiple decision trees to estimate missing values and outputs OOB (out of bag) imputation error estimates.

HERE IS YOUR ANSWER

HOPE IT IS HELPFUL FOR YOU

THANK YOU