C5.0 decision tree - c50 code called exit with value 1

Question

I am getting the following error

c50 code called exit with value 1

I am doing this on the titanic data available from Kaggle

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Answer 1

Here is what worked finally:-

Got this idea after reading this post

library(C50)

test$Survived <- NA

combinedData <- rbind(train,test)

combinedData$Survived <- factor(combinedData$Survived)

# fixing empty character level names 
levels(combinedData$Cabin)[1] = "missing"
levels(combinedData$Embarked)[1] = "missing"

new_train <- combinedData[1:891,]
new_test <- combinedData[892:1309,]

new_model <- C5.0(new_train[,-2],new_train$Survived)

new_model_predict <- predict(new_model,new_test)

submitC50 <- data.frame(PassengerId=new_test$PassengerId, Survived=new_model_predict)
write.csv(submitC50, file="c50dtree.csv", row.names=FALSE)

The intuition behind this is that in this way both the train and test data set will have consistent factor levels.