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ModelOriented / EMMA

Evaluation of Methods for dealing with Missing data in Machine Learning algorithms
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[test no. 2] missForest (PipeOpTaskPreproc) #54

Closed okcze closed 4 years ago

okcze commented 4 years ago

INFO [15:07:05.868] Applying learner 'imput_missForest.encodeimpact.classif.glmnet' on task 'Task 3722: hungarian (Supervised Classification)' (iter 2/5) Ostrzeżenie w poleceniu 'randomForest.default(x = obsX, y = obsY, ntree = ntree, mtry = mtry, ': The response has five or fewer unique values. Are you sure you want to do regression? Ostrzeżenie w poleceniu 'randomForest.default(x = obsX, y = obsY, ntree = ntree, mtry = mtry, ': The response has five or fewer unique values. Are you sure you want to do regression? Ostrzeżenie w poleceniu 'randomForest.default(x = obsX, y = obsY, ntree = ntree, mtry = mtry, ': The response has five or fewer unique values. Are you sure you want to do regression? Ostrzeżenie w poleceniu 'randomForest.default(x = obsX, y = obsY, ntree = ntree, mtry = mtry, ': The response has five or fewer unique values. Are you sure you want to do regression? Ostrzeżenie w poleceniu 'randomForest.default(x = obsX, y = obsY, ntree = ntree, mtry = mtry, ': The response has five or fewer unique values. Are you sure you want to do regression? Error in [.data.frame(final, , i) : nie wybrano kolumn

jjanborowka commented 4 years ago

If the column contains only missing values missForest will drop them what can't be done in the imputation stage. For example, if it happens in prediction but not in the training. Task will be different what will cause errors.