I was able to successfully run an RF model using some R code I was given. That is below and it includes snippet of my data too.
The only problem is that the way the code is written it only outputs a vector of probabilities and no data from the original test data set called "testset". So now I am trying to figure out how to output my probabilities along with the original data frame because I couldn't find a solution online. In other words I want it to be another column in the data set, like right after my FLSAStat column. That's so I can then output all of ittogether to a csv file.
Here's what I have:
#####################################################
# 1. SETUP DATA
#####################################################
mydata <- read.csv("train_test.csv", header=TRUE)
colnames(testset)
[1] "train" "Target" "ApptCode" "Directorate" "New_Discipline" "Series" "Adjusted.Age"
[8] "Adj.Service" "Adj.Age.Service" "HiEducLv" "Gender" "RetCd" "FLSAStat"
> head(testset)
train Target ApptCode Directorate New_Discipline Series Adjusted.Age Adj.Service Adj.Age.Service HiEducLv Gender
5909 0 NA IN Business Math Computer Science IT PSTS 54.44 10 64.44 Bachelor Male
5910 0 NA IN Computation Math Computer Science IT PSTS 51.51 15 66.51 Bachelor Male
5911 0 NA IN Physical and Life Sciences Physics PSTS 40.45 5 45.45 PHD Male
5912 0 NA IN Weapons and Complex Integ Physics PSTS 62.21 35 97.21 PHD Male
5913 0 NA IN Weapons and Complex Integ Physics PSTS 45.65 15 60.65 PHD Male
5914 0 NA FX Physical and Life Sciences Physics PSTS 36.13 5 41.12 PHD Male
RetCd FLSAStat
5909 TCP2 E
5910 TCP2 E
5911 TCP2 E
5912 TCP2 E
5913 TCP1 E
5914 TCP2 E
#create train and test sets
trainset = mydata[mydata$train == 1,]
testset = mydata[mydata$train == 0,]
#eliminate unwanted columns from train set
trainset$train = NULL
#####################################################
# 2. set the formula
#####################################################
theTarget <- "Target"
theFormula <- as.formula(paste("as.factor(",theTarget, ") ~ . "))
theFormula1 <- as.formula(paste(theTarget," ~ . "))
trainTarget = trainset[,which(names(trainset)==theTarget)]
testTarget = testset[,which(names(testset)==theTarget)]
#####################################################
# Random Forest
#####################################################
library(randomForest)
what <- "Random Forest"
FOREST_model <- randomForest(theFormula, data=trainset, ntree=500)
train_pred <- predict(FOREST_model, trainset, type="prob")[,2]
test_pred <- predict(FOREST_model, testset, type="prob")[,2]
display_results()
testID <- testset$case_id
predictions <- test_pred
submit_file = cbind(testID,predictions)
write.csv(submit_file, file="RANDOM4.csv", row.names = FALSE)
I think the problem is that I am lacking an additional line of code that does the merging of the predictions vector back into testSet. I'm guessing this this would go somewhere before the third to last line of code.