diff --git a/Schrick-Noah_Homework-6.R b/Schrick-Noah_Homework-6.R
index 238382c..21270e8 100644
--- a/Schrick-Noah_Homework-6.R
+++ b/Schrick-Noah_Homework-6.R
@@ -66,10 +66,62 @@ glm_fcn(train.X, train.y, 0)
 glm_fcn(train.X, train.y, 1)
 
 ## b. Repeat comparison using a graph with clusters
+if (!require("igraph")) install.packages("igraph")
+library(igraph)
+if (!require("Matrix")) install.packages("Matrix")
+library(Matrix) # bdiag 
+
+npc <-25 # nodes per cluster
+n_clust <- 4 # 4 clusters with 25 nodes each
+
+# no clusters
+g0 <- erdos.renyi.game(npc*n_clust, 0.2)
+plot(g0)
+
+matlist = list()
+for (i in 1:n_clust){ 
+  matlist[[i]] = get.adjacency(erdos.renyi.game(npc, 0.2))
+}
+
+# merge clusters into one matrix
+mat_clust <- bdiag(matlist) # create block-diagonal matrix
+
+## the following two things might not be necessary
+
+# check for loner nodes, connected to nothing, and join them to something
+k <- rowSums(mat_clust) 
+node_vector <- seq(1,npc*n_clust)
+for (i in node_vector){
+  if (k[i]==0){ # if k=0, connect to something random
+    j <- sample(node_vector[-i],1)
+    mat_clust[i,j] <- 1
+    mat_clust[j,i] <- 1
+  }
+}
+
+node_colors <- c(rep("red",npc), rep("green",npc), rep("blue",npc), rep("orange",npc))
+g1 <- graph_from_adjacency_matrix(mat_clust, mode="undirected", diag=F)
+plot(g1, vertex.color=node_colors)
 
 ## c. Use npdro and igraph to create knn
+my.k <- 3  # larger k, fewer clusters
+npdr.nbpairs.idx <- npdro::nearestNeighbors(t(train.X), 
+                                            # transpose does dist between predictors 
+                                            # without transpose does dist between samples
+                                            #nbd.method="multisurf", k=0, 
+                                            nbd.method = "relieff", 
+                                            nbd.metric="manhattan", 
+                                            k=my.k)
+knn.graph <- graph_from_edgelist(as.matrix(npdr.nbpairs.idx), 
+                                 directed=F)
+knn.graph <- simplify(knn.graph)
 
 ### Plot network
+plot.igraph(knn.graph,layout=layout_with_fr(knn.graph),
+            vertex.color="red",
+            vertex.size=3,vertex.label=NA, 
+            main="Manhattan, knn-graph")
+
 
 ## d. Add Laplace graph penalty