套索回归中 newx 的格式在 R 中给出错误

Question

我正在尝试实施套索线性回归。我训练了我的模型，但是当我尝试对未知数据进行预测时，出现以下错误：

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

我的数据摘要是：

我想预测未知的percent_gc。我最初使用 percent_gc 已知

的数据训练我的模型

 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)

然后我想做出 percent_gc 未知的预测。

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

这会产生我上面提到的错误。

我不明白 newX 应该是哪种格式才能摆脱这种帮助。见解将不胜感激。

Answer 1

我真的不知道如何构建合适的矩阵，但是包 glmnetUtils 提供了直接在数据框上拟合公式并进行预测的功能。有了这个我就可以预测值：

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)

套索回归中 newx 的格式在 R 中给出错误

Format of newx in Lasso regression gives error in R

r

machine-learning

lasso-regression