While building a random forest model on the dataset from the Kaggle problem ‘bike-sharing-demand’ I used to varImpPlot to see the important variables in my model->
fit <- randomForest(logreg ~ season+weather+temp +humidity +holiday+workingday+atemp +m+ hour + day_part+ year+day_type + windspeed, data=train,importance=TRUE, ntree=250)
and I get->
I can see that the topmost variable is the most significant but what is the difference between these two plots? They have different values on different positions. Which one to follow while selecting the significant variables?