Random Forests – Missing Data Leave a reply Welcome to your Random Forests - Missing Data What method does a random forest use to make an intial guess for missing values in the training data?The mean valueThe median valueProximity matrixAfter the initial guess for missing values in the training data, the missing value is then imputed based on theMost frequent non-missing value where frequency is weighted by proximityThe missing values are given a new categorical value that codes for missingProximity used in Random Forest imputation is based onHow often two observations are put into the same leaf nodeEuclidean distanceHow many features the two observations have in commonWhat is the first step for scoring new observations with missing data?Create copies of the data with the possible values for the targetUse a random forest to predict the missing valuesMedian imputation on the missing valuesPlease fill in the comment box below. Time is Up! Time's up
