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Author: Shimanto

Lasso Regression with python and R/Lasso Regression in R.R

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+library(MASS)
+##install.packages('corrplot')
+library(corrplot)
+library(glmnet)
+data("nlschools")
+str(nlschools)
+nlschools$class<-NULL
+p.cor<-cor(nlschools[,-5])
+corrplot.mixed(p.cor)
+ind<-sample(2,nrow(nlschools),replace=T,prob = c(0.7,0.3))
+train<-nlschools[ind==1,]
+test<-nlschools[ind==2,]
+train$COMB<-model.matrix( ~ COMB - 1, data=train ) #convert to dummy variable 
+test$COMB<-model.matrix( ~ COMB - 1, data=test )
+predictor_variables<-as.matrix(train[,2:4])
+language_score<-as.matrix(train$lang)
+lasso<-glmnet(predictor_variables,language_score,family="gaussian",alpha=1)
+print(lasso)
+plot(lasso,xvar = "lambda",label = T)
+
+plot(lasso,xvar='dev',label=T)
+test.matrix<-as.matrix(test[,2:4])
+lasso.y<-predict(lasso,newx = test.matrix,type = 'response',s=.02)
+plot(lasso.y,test$lang)
+lasso.resid<-lasso.y-test$lang
+mean(lasso.resid^2)
+
+
+