Hi,
I am doing predictive modelling of Multivariate Time series Data of a Motor
in R using various models such as Arima, H2O.Randomforest, glmnet, lm and
few other models.
I created a function to select a model of our choice and do prediction.
Model1 <- function(){
..
return()
}
Model2 <- function(){
...
return()
}
Model3 <- function(){
...
return()
}
main <- function(n){
if(n == 1) {
Model1()
}
else if(n == 2){
Model2()
}
else if(n == 3){
Model3()
}}
Now I am supposed to automate these models which gives RMSE and MAPE of
each model. I would like to provide scores (eg. out of 5) for each model
based on the performance. For example, if Arima gives a low RMSE than other
models, it will be scored high and the second lowest RMSE model will score
a less than Arima and so on.
And every time i run those models with different input Data [motor2, motor3
..], it must give the mean score of a model. what I mean to say is,
1. for motor1 it will give scores of each model, let's say *s1*.
2. for motor2 run it give scores of each model, and let's call it *s2*.
And i want a mean score of that model every time i run it with different
input. It is more like scoring and ranking method.
Are there any methods or packages in R that can give a glimpse of how it is
done? or any examples? Any suggestions would be very helpful.
Thank you.
Dhivya
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