Publications by Allen Baiju, Helena Lindsay, and Max St John
Analyzing Sentiments Surrounding the Recent Surge in Popularity of 'Lactate Threshold' Training Through Reddit Data
# Package names packages <- c("RedditExtractoR", "anytime", "magrittr", "ggplot2", "dplyr", "tidytext", "tidyverse", "igraph", "ggraph", "tidyr", "wordcloud2", "textdata", "sf", "tmap") # Install packages not yet installed installed_packages <- packages %in% rownames(installed.packages()) if (any(installed_packages == FALSE)) { install.packages(pa...
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Liveliness Example
Data Exploration #score <- read.csv("/Users/helenalindsay/Documents/Fall_23/CP8883/Computer_Vision/locations_qscore_combined.csv") score <- read.csv("/Users/helenalindsay/Documents/Fall_23/CP8883/Computer_Vision/Filtered_data/all_filtered.csv") score <- score %>% filter(loc.0 >= 33.62109 & loc.0 <= 33.90101 & loc.1 >= -84.55241 & loc.1 <...
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Liveliness Example
Data Exploration score <- read.csv("/Users/helenalindsay/Documents/Fall_23/CP8883/Computer_Vision/locations_qscore_combined.csv") score_sf <- score %>% st_as_sf(coords = c("loc.1", "loc.0"), crs = 4326) tmap_mode("view") map <- tm_basemap("Esri.WorldTopoMap")+ tm_shape(score_sf) + tm_dots(col = "num_votes", style="quantile", palette = 'viri...
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Liveliness Example
Data Exploration score <- read.csv("/Users/helenalindsay/Documents/Fall_23/CP8883/Computer_Vision/locations_qscore_combined.csv") score_sf <- score %>% st_as_sf(coords = c("loc.1", "loc.0"), crs = 4326) tmap_mode("view") map <- tm_basemap("Esri.WorldTopoMap")+ tm_shape(score_sf) + tm_dots(col = "num_votes", style="quantile", palette = 'viri...
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Major Assignment3- Analysis of Walkability Through OSM, GSV, and Computer Vision
This assignment consists of three main sections. In the first section, you need to select one Census Tract that you think is the most walkable and another one that you think is least walkable within Fulton and DeKalb Counties, GA. As long as the two Census Tracts are within the two counties, you can pick any two you want. If the area you want to us...
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Travel Time Analysis Using GTFS, OSM, and Census Data
Task description There are a few main components in this assignment - home location, road networks, transit network, and destination. We will simulate a journey that starts from the starting point (e.g., home), drives to nearest MARTA rail station, transfers to MARTA rail transit, and finally arrives at Midtown station (i.e., an employment center)....
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Travel Time Analysis Using GTFS, OSM, and Census Data
Task description There are a few main components in this assignment - home location, road networks, transit network, and destination. We will simulate a journey that starts from the starting point (e.g., home), drives to nearest MARTA rail station, transfers to MARTA rail transit, and finally arrives at Midtown station (i.e., an employment center)....
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Regression Tree, Random Forest
crime <- read.delim('/Users/helenalindsay/Documents/Fall_23/ISYE6501/hw5/uscrime.txt') Q10.1 Regression tree model #install.packages("rpart") library(rpart) tree_model <- rpart(Crime ~ ., data = crime) print(tree_model) ## n= 47 ## ## node), split, n, deviance, yval ## * denotes terminal node ## ## 1) root 47 6880928.0 905.0851 ## 2...
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Stepwise, Lasso, Elastic Net
Preparation of the library and dataset rm(list = ls()) # install.packages("MASS") # install.packages("glmnet") library(MASS) library(glmnet) uscrime <- read.table("/Users/helenalindsay/Documents/Fall_23/ISYE6501/hw7/uscrime.txt", header = TRUE) Stepwise Regression stepwiseAIC <- stepAIC(lm(Crime ~., data = uscrime), direction = "both") ## Start: ...
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Neighborhood Characteristics and Yelp Reviews
coffee <- read.csv("/Users/helenalindsay/Documents/Fall_23/CP8883/Mini4/coffee.csv")%>% select(-X) Plot 1 ggplot(data = coffee) + geom_boxplot(aes(x=factor(avg_rating), y=hhincome), fill = "white", color = "black")+ labs(x = "Average Rating", y = "Household Income") The plot implies that the higher household income relates ...
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