regresseur <- function(dataset) {
  # Chargement de l'environnement
  load("env.Rdata")
  cv.out <- cv.glmnet(as.matrix(reg.train.X),reg.train.y,alpha=1)
  #model.reg <- glmnet(as.matrix(reg.train.X),reg.train.y,lambda=cv.out$lambda.min,alpha=1)
  model.reg <- lm(reg.train.y ~ ., data = reg.train.X)
  data.test <- dataset[,reg.mask]
  predictions <- predict(model.reg, newdata = data.test)
  return(predictions)
}