14. 実⾏行行例例 > library(randomForest) > mdl <- randomForest(AGI~.-INSTWGHT, data=d.t) > print(mdl) ! Call: randomForest(formula = AGI ~ . - INSTWGHT, data = d.t) Type of random forest: classification Number of trees: 500 No. of variables tried at each split: 6 ! OOB estimate of error rate: 6.2% Confusion matrix: - 50000. 50000+. class.error - 50000. 187117 23 0.0001229026 50000+. 12353 29 0.997657890