#------------------ # Data Preparation #------------------ #Read datasets #Download the data from http://www.saedsayad.com/datasets/BikeRental.zip train <- read.csv("bike_rental_train.csv") test <- read.csv("bike_rental_test.csv") #Rows and Cols dim(train) dim(test) #Columns name colnames(train) colnames(test) #Show head(train) head(test) #Rows and Cols dim(train) dim(test) #Columns name colnames(train) colnames(test) #Show head(train) head(test) #-------------------- # K-Means Clustering #-------------------- library(ggplot2) #Clusters Clusters <- kmeans(train, 4, nstart = 20) summary(Clusters) #Plot Clusters.Lable <- as.factor(Clusters$cluster) ggplot(train, aes(temp, humidity, color = Clusters.Lable)) + geom_point()