I would like to asses the clusterability of my dataset of over 80.000 variables with Hopkins stastics. I started with n= 80.000. As n is obviously too high I reduce it to 10. But still received the same error message:
Error: cannot allocate vector of size 2511.3 Gb
clustab <- get_clust_tendency(WKA_ohneJB, 10, graph = TRUE, gradient = list(low = "red", + mid = "white", high = "blue"))
Apart from solving the issue, I have a further question: What is the highest number (n) you can take?
3. Import csv file
WKA_ohneJB <- read.csv("WKA_ohneJB.csv", header=TRUE, sep = ";", stringsAsFactors = FALSE)
4. Verify structure
str(WKA_ohneJB)
5. Descriptive Statistics for column BASKETS_NZ
mean(WKA_ohneJB[,"BASKETS_NZ"]) # 1.023035
median(WKA_ohneJB[,"BASKETS_NZ"]) # 1
var(WKA_ohneJB[,"BASKETS_NZ"]) # 0.06871633
sd(WKA_ohneJB[,"BASKETS_NZ"]) # 0.262138
range (WKA_ohneJB[,"BASKETS_NZ"]) # 0 49
hist (WKA_ohneJB[,"BASKETS_NZ"])
6. Summary descriptive statistics
summary(WKA_ohneJB)
7. Assessing clusterability of data set
clustab <- get_clust_tendency(WKA_ohneJB, 10, graph = TRUE, gradient = list(low = "red", mid = "white", high = "blue"))
WKA_ohneJB$hopkins_stat
