I have to fit model on given data set to predict closet appropriate fuel efficiency.

In excel file I have Model year which contain either 2017,2018,2019 or 2020

engine displacement which 41 different values

number of cylinder which contain 3,4,5,6,8,10,12,16

Aspiration which contain N ,tc, ot, ts, sc

number of gear which contain 1-10

Look up torque convertor which contain y or n

drive style which contain 4,r,f,a,p

Max ethanol which contain 10,15, 85

fuel type which contain g, gm, gp, gpr

and lastly fuel efficiency which contain several different values

and in total there are 1400 rows of data.

what model I should used or pruning should follow to get best predicted values in R programming language.

sample model <- lm(Comb.FE ~ .,data=train)

For sample data can checking this link :

https://www.kaggle.com/c/save-the-planet/data?select=RegressionTrain.csv