rm(list=ls())
train <- read.csv("Data/Mercedes-Benz/train.csv", header=TRUE)
test <- read.csv("Data/Mercedes-Benz/test.csv", header=TRUE)
#levels(train$X0) <- sort(c(levels(train$X0), c("ae", "ag", "an", "av", "bb", "p")))
#, "u", "v", "w", "x", "y", "z"
#levels(train$X0)
#levels(test$X0)
train1 <- train[, 2:ncol(train)]
#levels(train1$X0)
m <- lm(y~., data=train1)
m$xlevels[["X0"> <- union(m$xlevels[["X0">, levels(test$X0))
m$xlevels[["X2"> <- union(m$xlevels[["X2">, levels(test$X2))
m$xlevels[["X5"> <- union(m$xlevels[["X5">, levels(test$X5))
p <- predict(m, newdata=test[,2:ncol(test)], interval="prediction" )
result <- data.frame(ID=test[,"ID"], y=p[, "fit"])
write.csv(result, "result.csv", row.names=FALSE)
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