Publications by Ken Wood
Data Science Capstone in R - Week 3 Quiz
rm(list = ls()) library(quanteda) ## Package version: 2.1.2 ## Parallel computing: 2 of 4 threads used. ## See https://quanteda.io for tutorials and examples. ## ## Attaching package: 'quanteda' ## The following object is masked from 'package:utils': ## ## View library(data.table) library(dplyr) ## ## Attaching package: 'dplyr' ## The foll...
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Katz Backoff Prediction Model - Week 3
Applying the Katz Backoff Algorithm: As noted earlier, a corpus is a body of text from which we build and test LMs. rm(list = ls()) library(quanteda) ## Package version: 2.1.2 ## Parallel computing: 2 of 4 threads used. ## See https://quanteda.io for tutorials and examples. ## ## Attaching package: 'quanteda' ## The following object is masked fr...
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Katz Backoff Example
Example of Applying the Algorithm: The Little Corpus That Could As noted earlier, a corpus is a body of text from which we build and test LMs. To illustrate how the mathematical formulation of the KBO Trigram model works, it’s helpful to look at a simple corpus that is small enough to easily keep track of the n-gram counts, but large enough to ...
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R Programming - Week 4 Assignment
rm(list=ls(all=TRUE)) best <- function(state, outcome) { ## Read outcome data df <- read.csv("outcome-of-care-measures.csv", na.strings="Not Available",stringsAsFactors=FALSE, colClasses = "character") ## Check that state and outcome arguments are valid if ((state %in% df$State == TRUE) && (outcome %in% c("heart attack","heart failure",...
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Exploratory Data Analysis in R - Week 4 Assignment
# Load the raw data files. # These lines of code will take a little time to execute, so please be patient! NEI <- readRDS("exdata-data-NEI_data/summarySCC_PM25.rds") SCC <- readRDS("exdata-data-NEI_data/Source_Classification_Code.rds") merged_df <- merge(NEI,SCC,by="SCC") Questions We will address the following questions and tasks in our explor...
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R Programming - Week 3 Assignment
For large square matrices, it may take too long to compute the inverse, especially if it has to be computed repeatedly (e.g. in a loop). If the contents of the matrix do not change, it may make sense to cache the matrix inverse so that, when we need it again, it can be looked up in the cache rather than recomputed. In this Programming Assignment...
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Getting and Cleaning Data in R - Code Book Project
Fitbit devices use a 3-axis accelerometer to determine body movement and actions. This sensor also allows a device to determine the frequency, duration, intensity, and patterns of a person’s movement. Below is a table of tokens used in the dataset feature names and a brief description of each token. Token Description Body Signal based on the ...
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Getting and Cleaning Data in R - Week 2 Quiz
library(httr) library(jsonlite) # Question #1 # A. Find OAuth settings for github: # http://developer.github.com/v3/oauth/ oauth_endpoints("github") ## <oauth_endpoint> ## authorize: https://github.com/login/oauth/authorize ## access: https://github.com/login/oauth/access_token # B. To make your own application, register at # https:/...
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Getting and Cleaning Data in R - Week 3 Quiz
# Question #1 - Create a logical vector that identifies the households on greater than 10 acres who sold more than $10,000 worth of agriculture products. Assign that logical vector to the variable agricultureLogical. Apply the which() function like this to identify the rows of the data frame where the logical vector is TRUE. which(agricultureL...
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Developing Data Products in R - Week 3 Project
9/30/2020 Histogram of Housing Prices Box Plot of Saleprice vs. Home Condition Scatter Plot of Saleprice vs. Lot Area ...
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