The random forest model is simply voting the response variable to be one class and the error rate is 19.22%. The rate is impressive, but I'm just wondering how I can make the model favor the second row and column more? Thanks.
randomForest(formula = y1 ~ . - y1, data = df1, ntree = 20000) Type of random forest: classification Number of trees: 20000 No. of variables tried at each split: 7 OOB estimate of error rate: 19.22% Confusion matrix: 0 1 class.error 0 5219 0 0 1 1242 0 1