Jaehyeon Kim jaehyeon-kim

## jsbin.toganu.html
<!DOCTYPE html>
<html>
<head>
<script src="http://d3js.org/d3.v3.min.js"></script>
  <meta charset="utf-8">
  <title>JS Bin</title>
</head>
<body>

</body>

## downloadStockData
# assumes codes are known beforehand
codes <- c("MSFT", "1234")
urls <- paste0("http://www.google.com/finance/historical?q=NASDAQ:",
               codes,"&output=csv")
paths <- paste0(codes,"csv")
missing <- !(paths %in% dir(".", full.name = TRUE))
missing

# simple error handling in case file doesn't exists
downloadFile <- function(url, path, ...) {

## downloadMergeStockData
library(lubridate)
library(data.table)
library(plyr)
library(dplyr)

# create data folder
dataDir <- paste0("data",format(Sys.Date(),"_%Y_%m_%d"))
if(file.exists(dataDir)) {
      unlink(dataDir, recursive = TRUE)
      dir.create(dataDir)

## returnSummaryV2
library(lubridate)
library(stringr)
library(reshape2)
library(plyr)
library(dplyr)

# create data folder
dataDir <- paste0("data","_",format(Sys.Date(),"%Y-%m-%d"))
if(file.exists(dataDir)) {
      unlink(dataDir, recursive = TRUE)

## returnSummaryV3
library(knitr)
library(lubridate)
library(stringr)
library(reshape2)
library(plyr)

# create data folder
dataDir <- paste0("data","_",format(Sys.Date(),"%Y-%m-%d"))
if(file.exists(dataDir)) {
      unlink(dataDir, recursive = TRUE)

## addMean.R
## set up variables
size <- 36000
numUsers <- 4900
# roughly each user has 7 sessions
numSessions <- (numUsers / 7) - ((numUsers / 7) %% 1)

## create data frame
set.seed(123457)
userIds <- sample.int(numUsers, size=size, replace=TRUE)
ssIds <- sample.int(numSessions, size=size, replace=TRUE)

## doubleLoop
MyData <- data.frame(Year=seq(2000,2009))

# year variables
dim <- length(MyData$Year)
yMat <- matrix(NA, nrow=dim, ncol=dim)
for(i in 1:dim) {
      yMat[i,] <- rbind(t(MyData)) # transpose
}
yMat

## getUpdatedCM.R
#
# getUpdatedCM aims to extend a confusion matrix
# by adding model errors to the last column and use errors to the last row.
#
# Usage
# getUpdatedCM(cm)
#
# last modified on Feb 8, 2015
#

## mlUtils.R
#
# updateCM aims to extend a confusion matrix
# by adding model errors to the last column and use errors to the last row.
# Both square and non-square matrices are supported
#
# Usage
# set.seed(1)
# actual = ifelse(rnorm(100,0,1)<0,"low","high")
# fitted = ifelse(rnorm(100,1,5)<0,"low","high")
# updateCM(table(actual,fitted))

## cart.R
#
# 4 constructor functions are included and they create S3 objects of the CART model
# by the rpart, caret and mlr packages - the last two extends the first. They are
#
# - cartRPART()
# - cartCARET()
# - cartMLR()
# - cartDT()
#
# Both classification and regression are supported. Together with the relevant packages,
	<!DOCTYPE html>
	<html>
	<head>
	<script src="http://d3js.org/d3.v3.min.js"></script>
	<meta charset="utf-8">
	<title>JS Bin</title>
	</head>
	<body>

	</body>
	# assumes codes are known beforehand
	codes <- c("MSFT", "1234")
	urls <- paste0("http://www.google.com/finance/historical?q=NASDAQ:",
	codes,"&output=csv")
	paths <- paste0(codes,"csv")
	missing <- !(paths %in% dir(".", full.name = TRUE))
	missing

	# simple error handling in case file doesn't exists
	downloadFile <- function(url, path, ...) {
	library(lubridate)
	library(data.table)
	library(plyr)
	library(dplyr)

	# create data folder
	dataDir <- paste0("data",format(Sys.Date(),"_%Y_%m_%d"))
	if(file.exists(dataDir)) {
	unlink(dataDir, recursive = TRUE)
	dir.create(dataDir)
	library(lubridate)
	library(stringr)
	library(reshape2)
	library(plyr)
	library(dplyr)

	# create data folder
	dataDir <- paste0("data","_",format(Sys.Date(),"%Y-%m-%d"))
	if(file.exists(dataDir)) {
	unlink(dataDir, recursive = TRUE)
	library(knitr)
	library(lubridate)
	library(stringr)
	library(reshape2)
	library(plyr)

	# create data folder
	dataDir <- paste0("data","_",format(Sys.Date(),"%Y-%m-%d"))
	if(file.exists(dataDir)) {
	unlink(dataDir, recursive = TRUE)
	## set up variables
	size <- 36000
	numUsers <- 4900
	# roughly each user has 7 sessions
	numSessions <- (numUsers / 7) - ((numUsers / 7) %% 1)

	## create data frame
	set.seed(123457)
	userIds <- sample.int(numUsers, size=size, replace=TRUE)
	ssIds <- sample.int(numSessions, size=size, replace=TRUE)
	MyData <- data.frame(Year=seq(2000,2009))

	# year variables
	dim <- length(MyData$Year)
	yMat <- matrix(NA, nrow=dim, ncol=dim)
	for(i in 1:dim) {
	yMat[i,] <- rbind(t(MyData)) # transpose
	}
	yMat
	#
	# getUpdatedCM aims to extend a confusion matrix
	# by adding model errors to the last column and use errors to the last row.
	#
	# Usage
	# getUpdatedCM(cm)
	#
	# last modified on Feb 8, 2015
	#
	#
	# updateCM aims to extend a confusion matrix
	# by adding model errors to the last column and use errors to the last row.
	# Both square and non-square matrices are supported
	#
	# Usage
	# set.seed(1)
	# actual = ifelse(rnorm(100,0,1)<0,"low","high")
	# fitted = ifelse(rnorm(100,1,5)<0,"low","high")
	# updateCM(table(actual,fitted))
	#
	# 4 constructor functions are included and they create S3 objects of the CART model
	# by the rpart, caret and mlr packages - the last two extends the first. They are
	#
	# - cartRPART()
	# - cartCARET()
	# - cartMLR()
	# - cartDT()
	#
	# Both classification and regression are supported. Together with the relevant packages,