Zach Deane-Mayer zachmayer

AI executive & Kaggle Grandmaster: 15+ years building with AI and ML.

zachmayer / test.html

Last active December 12, 2015 04:38

	<html>
	<head>
	<title>Test</title>
	<meta name="viewport" content="user-scalable=no, width=device-width, initial-scale=1.0, maximum-scale=1.0"/>
	<meta name="apple-mobile-web-app-capable" content="yes" />
	<meta name="apple-mobile-web-app-status-bar-style" content="black" />
	<link rel="apple-touch-icon" href="icon.png"/>
	<style type="text/css">
	body{ margin: 0px;}
	</style>

zachmayer / 1. Load Data.R

Last active December 11, 2015 16:48

	#Load the dataset, adjust, and convert to monthly returns
	set.seed(42)
	library(quantmod)
	getSymbols('^GSPC', from='1990-01-01')
	GSPC <- adjustOHLC(GSPC, symbol.name='^GSPC')
	GSPC <- to.monthly(GSPC, indexAt='lastof')
	Target <- ClCl(GSPC)

zachmayer / TS5.R

Created January 25, 2013 00:16

	#Download S&P 500 data, adjust, and conver to monthly
	set.seed(42)
	library(quantmod)
	getSymbols('^GSPC', from='1990-01-01')
	GSPC <- adjustOHLC(GSPC, symbol.name='^GSPC')
	GSPC <- to.monthly(GSPC, indexAt='lastof')
	Target <- ClCl(GSPC)

	#Calculate some co-variates
	periods <- c(3, 6, 9, 12)

zachmayer / multiclass.R

Created July 6, 2012 16:46

Multi Class Error Metrics

	#Multi-Class Summary Function
	#Based on caret:::twoClassSummary
	require(compiler)
	multiClassSummary <- cmpfun(function (data, lev = NULL, model = NULL){

	#Load Libraries
	require(Metrics)
	require(caret)

	#Check data

zachmayer / Backtesting Part 5.R

Created June 25, 2012 22:19

Backtesting Part 5


	rm(list = ls(all = TRUE))
	memory.limit(size = 4095)

	#Get Data
	library(quantmod)
	getSymbols('^GSPC',from='1900-01-01')
	myStock <- Cl(GSPC)
	bmkReturns <- dailyReturn(myStock, type = "arithmetic")

zachmayer / InstallPackages.R

Created June 19, 2012 14:33

Install Packages

install.packages(c('caret', 'doParallel', 'ggplot2', 'data.table', 'caTools', 'XML', 'quantmod'), dependencies=TRUE)

zachmayer / cv.ts 4.R

Created June 11, 2012 17:52

Time series cross-validation 4: forecasting the S&P 500

	#Setup
	rm(list = ls(all = TRUE))
	setwd('path.to/cv.ts')

	#Load Packages
	require(forecast)
	require(doParallel)
	source('R/cv.ts.R')
	source('R/forecast functions.R')

zachmayer / 1.parDEoptim.R

Created January 23, 2012 14:28

parDEoptim

	setClass("parDEoptim", representation(optim="list", member="list"))

	parDEoptim <- function (fn, lower, upper, n=1, control = DEoptim.control(), .packages=NULL, ...) {
	library("DEoptim")
	library("foreach")
	segSizes <- (upper-lower)/n
	segments <- lapply(1:n, function(x){
	lower+segSizes*(x-1)
	})

zachmayer / 1. Functions.R

Created December 29, 2011 18:05

Forecasting S&P 500

	#Function to cross-validate a time series.
	cv.ts <- function(x, FUN, tsControl, xreg=NULL, ...) {

	#Load required packages
	stopifnot(is.ts(x))
	stopifnot(is.data.frame(xreg) \| is.matrix(xreg) \| is.null(xreg))
	stopifnot(require(forecast))
	stopifnot(require(foreach))
	stopifnot(require(plyr))

zachmayer / cv.ts.R

Created December 12, 2011 16:26

Time series cross-validation 3

	#Function to cross-validate a time series.
	cv.ts <- function(x, FUN, tsControl, xreg=NULL, ...) {

	#Load required packages
	stopifnot(is.ts(x))
	stopifnot(is.data.frame(xreg) \| is.matrix(xreg) \| is.null(xreg))
	stopifnot(require(forecast))
	stopifnot(require(foreach))
	stopifnot(require(plyr))