adding lambda2 term for lasso loop

Schrick-Noah_Homework-6.R

@@ -100,7 +100,9 @@ run_comparison <- function(bundled_data){
 run_comparison(bundled_data)
 ## b. Repeat comparison using a graph with clusters
 source("Schrick-Noah_graphs.R")
-bundled_graph_data <- sim_graph_data()
+bundled_graph <- sim_graph_data()
+bundled_graph_data <- bundled_graph$bundled_graph_data
+g1 <- bundled_graph$g1
 
 run_comparison(bundled_graph_data)
 
@@ -125,25 +127,15 @@ plot.igraph(knn.graph.g,layout=layout_with_fr(knn.graph.g),
             main="Manhattan, knn-graph from simulated data
             with erdos-renyi graph structure")
 
-### Bundled Data
-npdr.nbpairs.idx <- npdro::nearestNeighbors(t(bundled_data$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)
+is_isomorphic_to(g1, knn.graph.g)
+plot(g1)
+
+clusters <- cluster_louvain(knn.graph.g)
+plot(knn.graph.g, mark.groups=clusters)
 
-### 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 from simulated data")
 
 ## d. Add Laplace graph penalty
+Lhat <- laplacian_matrix(g1, normalized = TRUE)
 
 ### Find resulting beta coeffs
 

Schrick-Noah_Ridge-LASSO-Regression.R

@@ -1,3 +1,6 @@
+if (!require("numbers")) install.packages("numbers")
+library(numbers)
+
 penalized_loss <- function(X, y, beta, lam, alpha=0){
   # y needs to be 0/1
   # beta: regression coefficients
@@ -55,7 +58,7 @@ lasso_betas <- function(X,y,beta_init=NULL){
 }
 
 # Adjust betas
-lasso_coeff <- function(X, y, lambda=0, tol=1e-8){
+lasso_coeff <- function(X, y, lambda=0.03125, tol=1e-2){
   unpen_beta <- lasso_betas(X, y, beta_init=numeric(101))
   old_loss <- unpen_beta$loss
   lasso_converged <- FALSE
@@ -79,6 +82,9 @@ lasso_coeff <- function(X, y, lambda=0, tol=1e-8){
     }
     unpen_beta <- lasso_betas(X,y,beta_init=beta_LS$par)
     lasso_converged <- abs(unpen_beta$loss - old_loss) < tol
+    if(mod(loop_count, 25) == 0){
+      cat("Loop:", loop_count, "Convergence:", abs(unpen_beta$loss - old_loss),"\n")
+    }
     old_loss <- unpen_beta$loss
     loop_count <- loop_count + 1
   }

Schrick-Noah_graphs.R

@@ -39,5 +39,5 @@ sim_graph_data <- function(){
   
   ### Dataset with g1
   bundled_graph_data <- create_data(graph.structure=g1)
-  return(bundled_graph_data)
+  return(list(bundled_graph_data=bundled_graph_data,g1=g1))
 }