Format of newx in Lasso regression gives error in R

Question

I am trying to implement lasso linear regression. I train my model but when I try to make prediction on unknown data it gives me the following error:

 Error in cbind2(1, newx) %*% nbeta : 
     invalid class 'NA' to dup_mMatrix_as_dgeMatrix

Summary of my data is:

I want to predict the unknown percent_gc. I initially train my model using data for which percent_gc is known

 set.seed(1)

 ###training data
 data.all <- tibble(description = c('Xylanimonas cellulosilytica XIL07, DSM 15894','Teredinibacter turnerae T7901',
                            'Desulfotignum phosphitoxidans FiPS-3, DSM 13687','Brucella melitensis bv. 1 16M'),
            phylum = c('Actinobacteria','Proteobacteria','Proteobacteria','Bacteroidetes'),
            genus = c('Acaryochloris','Acetohalobium','Acidimicrobium','Acidithiobacillus'),
            Latitude = c('63.93','69.372','3.493.11','44.393.704'),
            Longitude = c('-22.1','88.235','134.082.527','-0.130781'),
            genome_size = c(8361599,2469596,2158157,3207552),
            percent_gc = c(34,24,55,44),
            percent_psuedo = c(0.0032987747,0.0291222313,0.0353728489,0.0590663703),
            percent_signalpeptide = c(0.02987198,0.040607055,0.048757170,0.061606859))

  ###data for prediction
  data.prediction <- tibble(description = c('Liberibacter crescens BT-1','Saprospira grandis Lewin',
                            'Sinorhizobium meliloti AK83','Bifidobacterium asteroides ATCC 25910'),
            phylum = c('Actinobacteria','Proteobacteria','Proteobacteria','Bacteroidetes'),
            genus = c('Acaryochloris','Acetohalobium','Acidimicrobium','Acidithiobacillus'),
            Latitude = c('39.53','69.372','5.493.12','44.393.704'),
            Longitude = c('20.1','-88.235','134.082.527','-0.130781'),
            genome_size = c(474832,2469837,2158157,3207552),
            percent_gc = c(NA,NA,NA,NA),
            percent_psuedo = c(0.0074639239,0.0291222313,0.0353728489,0.0590663703),
            percent_signalpeptide = c(0.02987198,0.040607055,0.048757170,0.061606859))

x=model.matrix(percent_gc~.,data.all)
y=data.all$percent_gc

cv.out <- cv.glmnet (x, y, alpha = 1,family  = "gaussian")
best.lambda= cv.out$lambda.min

fit <- glmnet(x,y,alpha=1)

I then want to make predictions for which percent_gc in not known.

newX = matrix(data = data.prediction %>% select(-percent_gc)) 
data.prediction$percent_gc <- 
 predict(object = fit ,type="response", s=best.lambda, newx=newX)

And this generates the error I mentioned above.

I don't understand which format newX should be in order to get rid of this help. Insights would be appreciated.

Hi. Providing your daras as image is not very helpful for helping you with your problem. Please provide a reproducible, minimal example (Good description:https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) so that we can reproduce your problem — Julian_Hn, Apr 02 '19 at 13:29
Sorry, I added a two data frames with data in it. If you run my code you will be able to get the same error. — Shafa Haider, Apr 02 '19 at 13:54

score 1 · Accepted Answer · answered Apr 02 '19 at 14:18

I could not really figure out how to construct a appropiate matrix, but package glmnetUtils provides functionality to directly fit a formula on a dataframe and predict. With this I got it to predict values:

library(glmnetUtils)
fit <- glmnet(percent_gc~.,data.all,alpha=1)
cv.out <- cv.glmnet (percent_gc~.,data.all, alpha = 1,family  = "gaussian")
best.lambda= cv.out$lambda.min

predict(object = fit,data.prediction,s=best.lambda)

Format of newx in Lasso regression gives error in R

1 Answers1