Final Project (R programming)

##### DO NOT hard code the working directory ##### only use below format to read the data data_independent <- read.csv(file = 'data - for student - independent variables.csv') data_dependent <- read.csv(file = 'data - for student - dependent variable.csv') y <- data_dependent$AmountWines first_name<-'Yan' last_name<-'Lang' ##### This example is using average to predict AmountWines mean.y<-mean(y) ##### write the prediction function name "model" model<-function(new_data_independent) { pred<-vector(length=nrow(new_data_independent)) # set up the output prediction for(i in 1:nrow(new_data_independent)) { # in this example, you only use the average of y to predict. # In actual work, you need to define what variables to use to predict in this function pred[i] <- mean.y } return(pred) } ##### note the input "new_data" needs to be in the SAME format as data_independent ##### note that in this example, it only used mean of y to predict. It did not use any independent variable new_data <- data.frame(data_independent$Kid_home, data_independent$AmountMeat) ##### use below code to calculate your RMSE preds <- model(new_data) rmse<- sqrt(mean((y - preds)^2)) output<-data.frame(first_name,last_name,rmse) write.table(output,file="finaloutput.csv",append=TRUE,col.names=FALSE,row.names=TRUE,sep=",") ##### keep below code, but don't run it when you are checking your codes, it is for my machine source("predictdata.R")