--- a/aggregation.R	Wed Oct 26 02:33:15 2016 -0400
+++ b/aggregation.R	Wed Oct 26 17:31:45 2016 -0400
@@ -12,9 +12,20 @@
 suppressWarnings(suppressMessages(library(randomForest)))
 library(e1071)
 suppressWarnings(suppressMessages(library(glmnet)))
+options(warn=-1)
 ############################ helper functions #######################
 
 ##### Genetic algorithm
+
+# compute r2 by computing the classic formula
+# compare the sum of square difference from target to prediciton
+# to the sum of square difference from target to the mean of the target
+r2 <- function(target, prediction) {
+  sst <- sum((target-mean(target))^2)
+  ssr <- sum((target-prediction)^2)
+  return(1-ssr/sst)
+}
+
 optimizeOneIndividual <- function(values, trueValue) {
   # change the value into a function
   f <- function(w) {sum(values * w/sum(w))}
@@ -282,7 +293,7 @@
                      out = out, prediction = prediction, model=model)
        },
        lasso={
-         aggregateLASSO(classifiers = classifPrediction, target = phenotype,
+         aggregateLASSO(classifiers = data.matrix(classifPrediction), target = phenotype,
                      out = out, prediction = prediction, model=model)
        },
        rf={