October 2019
Intermediate to advanced
316 pages
9h 45m
English
Content preview from R Bioinformatics Cookbook
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How to do it...
Predicting classes with random forests can be done using the following steps:
- Prepare a training set from the iris data:
library(randomForest)train_rows <- sample(nrow(iris), 0.8 * nrow(iris), replace = FALSE) train_set <- iris[train_rows, ] test_set <- iris[-train_rows, ]
- Build a model on the training data:
model <- randomForest(Species ~ . , data = train_set, mtry = 2)
- Use the model to make predictions on the test data:
test_set_predictions <- predict(model, test_set, type = "class") caret::confusionMatrix(test_set_predictions, test_set$Species)
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