rapport régression fini

predicteurs.R

 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)

prepaDataReg.R

@@ -8,7 +8,7 @@ reg.data <- read.table("tp3_a18_reg_app.txt")
 reg.fit <-regsubsets(y ~ .,data=reg.data,method="exhaustive",nvmax=50, really.big = T)
 subsets <- summary(reg.fit)
 
-mask <- subsets$which[,2:51]
+reg.mask <- subsets$which[24,2:51]
 
-reg.train.X <- reg.data[,mask]
+reg.train.X <- reg.data[,reg.mask]
 reg.train.y <- reg.data[,y]
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