zachmayer

program hello
  print *, "Hello World!"
end program hello

zachmayer

#Define the problem
t1 <- Sys.time()
set.seed(1)
n_nodes <- 300000L
n_edges <- 900000L
nodes <- 1L:n_nodes
edge_node_1 <- sample(nodes, n_edges, replace=TRUE)
edge_node_2 <- sample(nodes, n_edges, replace=TRUE)

#Sparse matrix

zachmayer

install.packages(c("caret","reshape2","plyr","caTools"),dependencies=c("Depends", "Imports", "LinkingTo", "Suggests", "Enhances"))

zachmayer

####################################
# Training parameters
####################################
MyTrainControl=trainControl(
		method = "repeatedCV",
		number=10,
		repeats=5,
		returnResamp = "all",
		classProbs = TRUE,
		summaryFunction=twoClassSummary

zachmayer

#Setup
rm(list = ls(all = TRUE)) #CLEAR WORKSPACE

#Directory
setwd("~/Overfitting")

#Load Required Packages
library('caTools')
library('caret')
library('glmnet')

zachmayer

library(quantmod)
getSymbols(c('AHETPI','CES0500000003','CPIAUCSL','GASREGM'),src = "FRED")
getSymbols('XAU/USD',src = "oanda")

#Definitions:
#AHETPI = Average Hourly Earnings of Production and Nonsupervisory Employees: Total Private
#CES0500000003 = Average Hourly Earnings of All Employees: Total Private
#CPIAUCSL = Consumer Price Index for All Urban Consumers: All Items
#GASREGM = US Regular All Formulations Gas Price
#XAUUSD USD per 1 oz of gold.  Last 500 days only

zachmayer

multiRF <- function(x,...) {
	foreach(i=x,.combine=combine,.packages='randomForest',
	.export=c('X','Y'),.inorder=FALSE) %dopar% {
		randomForest(X,Y,mtry=i,...)
	} 
}
multiRF(c(rep(3,10),rep(4,10),rep(5,10)),ntree=500)

zachmayer

## Load googlepredictionapi and dependent libraries
library(rjson)
library(RCurl)
library(googlepredictionapi)

#Save dataframe to a file, upload to google storage, and train a model
write.csv(iris,'iris.csv')
model <- PredictionApiTrain(data='iris.csv', remote.file="gs://rdata/iris")

#Summarize model and predict for new data

zachmayer

#Actual Recessions
getSymbols('USREC',src='FRED') 
USREC <- USREC["1997-07-01::",] #Start from same period

#Compare recession now to warning last month
library(caret)
OneMonth <- Lag(P.Rec)
compare <- na.omit(merge(OneMonth,USREC))
confusionMatrix(compare[,1],compare[,2],positive = '1')

zachmayer

cor(iris[-5])
pairs(iris[-5], bg=iris$Species, pch=21)