Publications by Ken Wood
Regression Models in R: Week 4 Quiz
Question #1 Consider the space shuttle data in the MASS library. Consider modeling the use of the autolander as the outcome (variable name use). Fit a logistic regression model with autolander (variable ‘auto’) use (labeled as “auto” 1) versus not (0) as predicted by wind sign (variable wind). Give the estimated odds ratio for autolander ...
2004 sym R (4832 sym/26 pcs)
Practical Machine Learning in R - Quiz 4
Clear out all previous R sessions… rm(list = ls()) Question 1 Load the vowel.train and vowel.test data sets: library(caret) ## Loading required package: lattice ## Loading required package: ggplot2 library(gbm) ## Loaded gbm 2.1.8 library(ElemStatLearn) data(vowel.train) data(vowel.test) Set the variable y to be a factor variable in both the t...
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Data Science Capstone in R - Week 1 Quiz
Question 1 The en_US.blogs.txt file is how many megabytes? file.info("final/en_US/en_US.blogs.txt") ## size isdir mode mtime ## final/en_US/en_US.blogs.txt 210160014 FALSE 644 2014-07-22 05:13:05 ## ctime atime uid gid ## final/en_US/en_US.blog...
731 sym R (2660 sym/29 pcs)
Data Science Capstone in R - Week 2 Analysis
Instructions The goal of this project is to display that we’ve gotten used to working with the data and that we are on track to create your prediction algorithm. This report (to be submitted on R Pubs (http://rpubs.com/)) explains our exploratory analysis and our goals for the eventual app and algorithm. This document should be concise and expl...
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Practical Machine Learning in R - Course Project
Background Using devices such as Jawbone Up, Nike FuelBand, and Fitbit it is now possible to collect a large amount of data about personal activity relatively inexpensively. These type of devices are part of the quantified self movement – a group of enthusiasts who take measurements about themselves regularly to improve their health, to find pa...
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Practical Machine Learning in R - Quiz 3
Question 1 Load the cell segmentation data from the AppliedPredictiveModeling package using the commands: rm(list = ls()) library(AppliedPredictiveModeling) data(segmentationOriginal) library(caret) ## Loading required package: lattice ## Loading required package: ggplot2 Subset the data to a training set and testing set based on the Case varia...
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Reproducible Research in R - Week 2 Assignment
Loading and preprocessing the data Show any code that is needed to: Load the data (i.e. read.csv()). Process/transform the data (if necessary) into a format suitable for your analysis. knitr::opts_chunk$set(echo = TRUE) library(chron) # Read in the data file. df <- read.csv("activity.csv") # Convert 'date' column to datetime variable. df$d...
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Practical Machine Learning in R - Quiz 2
Question 1 library(caret) ## Loading required package: lattice ## Loading required package: ggplot2 library(AppliedPredictiveModeling) data(AlzheimerDisease) What are the set of commands that will create non-overlapping training and test sets with about 50% of the observations assigned to each? adData = data.frame(diagnosis,predictors) trainIndex...
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Regression Models - Course Project
Executive Summary Motor Trend, a magazine about the automobile industry, wants to look at a data set of a collection of cars to learn more about mileage. They are interested in exploring the relationship between a set of variables and miles per gallon (MPG) (outcome). Specifically, they are interested in answering the following two questions: �...
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Reproducible Research in R - Week 4 Assignment
Executive Summary Storms and other severe weather events can cause both public health and economic problems for communities and municipalities. Many severe events can result in fatalities, injuries, and property damage, and preventing such outcomes to the extent possible is a key concern. This analysis leverages the U.S. National Oceanic and Atmo...
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