Publications by Joey Campbell
Case Study WHO Example Questions
This code is repeated from the Tidy Data Case Study because it is needed by the exercises. library(tidyverse) who1 <- who %>% gather(new_sp_m014:newrel_f65, key = "key", value = "cases", na.rm = TRUE) glimpse(who1) Observations: 76,046 Variables: 6 $ country [3m[38;5;246m<chr>[39m[23m "Afghanistan", "Afghanistan", "Afghanistan", "Afghanist...
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Tidy Data Case Study
Let’s pull together everything you’ve learned to tackle a realistic data tidying problem. The tidyr::who dataset contains tuberculosis (TB) cases broken down by year, country, age, gender, and diagnosis method. The data comes from the 2014 World Health Organization Global Tuberculosis Report, available at http://www.who.int/tb/country/data/do...
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googleVis
R Interface to Google Charts The googleVis package provides an interface between R and the Google’s charts tools. It allows users to create web pages with interactive charts based on R data frames. Charts are displayed locally via the R HTTP help server. A modern browser with Internet connection is required and for some charts a Flash player. T...
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Plotly
Getting Started with Plotly for R Plotly is a free and open-source graphing library for R. Getting Started with Plotly for R Plotly is a free and open-source graphing library for R. Plotly’s R graphing library makes interactive, publication-quality graphs. Getting Started with Plotly for R Plotly is a free and open-source graphing library ...
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SVM with CARET
The Support Vector Machine (or SVM) is a useful classification technique. Support vector machine methods can handle both linear and non-linear class boundaries. It can be used for both two-class and multi-class classification problems. In real life data, the separation boundary is generally nonlinear. Technically, the SVM algorithm perform a non-...
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Lab 8 Trees Based Method
Fitting Classification Trees Recursive partitioning is a fundamental tool in data mining. It helps us explore the stucture of a set of data, while developing easy to visualize decision rules for predicting a categorical (classification tree). Classification (as described by Brieman, Freidman, Olshen, and Stone) can be generated through the rpart ...
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STA4143_mt_caret
library('tidyverse') library('caret') library('modelr') set.seed(303) Part 2: Regression (40 Points) The table below displays catalog-spending data for the first few of 200 randomly selected individuals from a very large (over 20,000 households) data base.1 The variable of particular interest is catalog spending as measured by the Spending Ra...
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ISLR Chapter 5 Problem 5
suppressPackageStartupMessages(library('ISLR')) package 㤼㸱ISLR㤼㸲 was built under R version 3.6.3 summary(Default) default student balance income No :9667 No :7056 Min. : 0.0 Min. : 772 Yes: 333 Yes:2944 1st Qu.: 481.7 1st Qu.:21340 Median : 823.6 Median :34553 ...
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estimating model accuracy on iris
Estimating Model Accuracy We have considered model accuracy before in the configuration of test options in a test harness. You can read more in the post: How To Choose The Right Test Options When Evaluating Machine Learning Algorithms. In this post you can going to discover 5 different methods that you can use to estimate model accuracy. They are...
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scales76_Demo
suppressPackageStartupMessages(library("tidyverse")) package 㤼㸱tidyverse㤼㸲 was built under R version 3.6.3 suppressPackageStartupMessages(library("modelr")) package 㤼㸱modelr㤼㸲 was built under R version 3.6.3 suppressPackageStartupMessages(library("lubridate")) 1. Why doesn’t the following code override the default scale? df <- ...
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