joelkr’s gists

joelkr / Setup.R

Created June 22, 2014 23:11

R data munging file for UC Irvine Cardiac Arrythmia File

	cardiac <- read.csv("arrhythmia.data", header=F, na.strings="?")
	colnames(cardiac)[1:280] <- c("Age","Gender_Nom","Height","Weight","QRS_Dur",
	"P-R_Int","Q-T_Int","T_Int","P_Int","QRS","T","P","QRST","J","Heart_Rate",
	"Q_Wave","R_Wave","S_Wave","R_Prime","S_Prime","Int_Def","Rag_R_Nom",
	"Diph_R_Nom","Rag_P_Nom","Diph_P_Nom","Rag_T_Nom","Diph_T_Nom",
	"DII00", "DII01","DII02", "DII03", "DII04","DII05","DII06","DII07","DII08","DII09","DII10","DII11",
	"DIII00","DIII01","DIII02", "DIII03", "DIII04","DIII05","DIII06","DIII07","DIII08","DIII09","DIII10","DIII11",
	"AVR00","AVR01","AVR02","AVR03","AVR04","AVR05","AVR06","AVR07","AVR08","AVR09","AVR10","AVR11",
	"AVL00","AVRL1","AVL02","AVL03","AVL04","AVL05","AVL06","AVL07","AVL08","AVL09","AVL10","AVL11",
	"AVF00","AVF01","AVF02","AVF03","AVF04","AVF05","AVF06","AVF07","AVF08","AVF09","AVF10","AVF11",

joelkr / CollaborativeFiltering.R

Created June 22, 2014 23:55

R Functions for Collaborative Filtering Cardiac Arrythmia Data

	# Cost and gradient functions for optim(). These are a port of Coursera
	# Machine Learning course topic Collaborative Filtering from MATLAB
	# to R.

	# Cost Function
	coFilterCost <- function (params, npatients, nleads, nreadings,Y, R, lambda)
	{
	# params: X and Theta flattened to vector
	# npatients, nleads, nreadings: number of patients, leads, and numeric
	# fields in data

joelkr / Test.R

Last active August 29, 2015 14:02

Testing Collaborative Filtering on the Cardiac Arrythmia Data

	# Try setting up a smaller test set

	# Variables to set how large a square of data to test
	npatients <- 4
	nreadings <- 8
	# We are still not converging in 500 trials. Perhaps we have too many unknowns.
	#nleads <- 10
	nleads <- 12
	load("cardiacSetup.rda")

joelkr / BayesProbability.R

Created September 5, 2014 22:36

	# BayesProbability.R

	#set.seed(49)

	# Build a dummy dictionary
	a <- letters
	b <- letters
	tokens <- apply(expand.grid(a, b), 1, function(x) paste(x, collapse=""))
	# Number of tokens to use 1-676
	tl <- 100

joelkr / handy.R

Created February 6, 2015 16:48

NASA HANDY Model in R

	library(deSolve)

	handyMod <- function(Time, State, Pars) {
	with(as.list(c(State, Pars)), {
	# First calculate threshold below which famine begins
	# rho = minimum required consumption
	wThresh = rho * popC + rho * kappa * popE
	# Check to avoid dividing by zero then estimate consumption of
	# commons = cC and elites = cE
	if(wThresh > 0) {

joelkr / Dockerfile

Created March 3, 2017 15:38

Docker file for kaggle

	FROM ubuntu:16.04
	#FROM ubuntu:14.04
	# Extended and moved to python 3 based on image:
	#MAINTAINER Wise.io, Inc. <[email protected]>

	ENV DEBIAN_FRONTEND noninteractive

	ENV PATH /anaconda/bin:$PATH
	# For image inheritance.
	ONBUILD ENV PATH /anaconda/bin:$PATH

joelkr / docker-compose.yml

Created March 3, 2017 16:06

docker-compose.yml for kaggle