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Could you please run the following codes and interpret the results in R programme by giving some numeric examples ? # Define a function to

Could you please run the following codes and interpret the results in R programme by giving some numeric examples ? # Define a function to implement the Minimum Violators Algorithm minimum_violators_algorithm <- function(components, roots, Ts, K, g){ # Step 1: Create a singleton cluster for each component clusters <- lapply(components, function(comp) list(components = comp))
# Initialize set Q with roots of all clusters except the one containing the final product Q <- setdiff(roots, tail(roots,1))
# Initialize set r with the root of the final product cluster r <- tail(roots,1)
while (length(Q)>0){ # Step 2: Find a cluster i in Q with minimal K(Ci)/ g(Ci) min_ratio <- Inf min_cluster <- NULL
for (i in Q){ Ci <- clusters[[i]] ratio <- K(Ci)/ g(Ci)
if (ratio < min_ratio ||(ratio == min_ratio && length(Ci$components)< length(min_cluster$components))){ min_ratio <- ratio min_cluster <- Ci }}
# Step 3: Remove i from Q Q <- setdiff(Q, which(roots == min_cluster$components[[1]]))
# Check the condition K(Ci')/ g(Ci')>= K(Ci)/ g(Ci) if (K(min_cluster)/ g(min_cluster)>= K(clusters[[r]])/ g(clusters[[r]])){ # Add i to r r <- c(r, min_cluster$components[[1]])} else { # Collapse cluster i into cluster r clusters[[r]]$components <- c(clusters[[r]]$components, min_cluster$components)}}
# Output the optimal clusters optimal_clusters <- lapply(r, function(root) clusters[[root]]) return(optimal_clusters)}

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