Publications by Matthew Lucich
Assignment Week 9 - Web APIs
library(tidyverse) library(jsonlite) Overivew The objective is to create an interface with one of the NY Times APIs, read in the JSON response, and convert it into a data frame. I chose to call the archive API, specifically querying articles from April 1921, then filtering the results further for articles from April 10th 1921. Finally, to make t...
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GoodReads.com Recommender System
Introduction It may seem counterintuitive to have a recommender system that intentionally does not recommend items the users will likely want most, nevertheless in the right circumstances I believe this cannot only be beneficial to the users, but to the organization as well. The proliferation of echo chambers in recent years is often attributed t...
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Assignment 10 – Sentiment Analysis
library(tidyverse) library(ggplot2) library(tidytext) library(textdata) library(janeaustenr) library(gutenbergr) library(SentimentAnalysis) Overview The objective was to re-create the code supplied in chapter 2 of Text Mining with R, then to extend the exercise with a new corpus and lexicon. Recreating the analysis in chapter 2 came with no issu...
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Data 605 HW1
Build the first letters for both your first and last name using point plots in R. # ML x <- c(rep(-1.5,500), seq(-0.75,-1.5,length.out=500), seq(-0.75,0,length.out=500), rep(1,500), seq(2,1,length.out=500), rep(0,500)) y <- c(seq(-2,1,length.out=500), seq(-2,1,length.out=500), seq(-2,1,length...
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Data 621 - Final
Data Cleaning df_wb <- read_csv("world-bank.csv") #glimpse(df_wb) # Filter for Brazil, Russia, India, China, and South Africa df_brics <- df_wb %>% filter(grepl("BRA|CHN|IND|RUS|ZAF", `Country Code`)) variables_to_include <- "NY.GDP.PCAP.KD.ZG|FS.AST.CGOV.GD.ZS|FP.CPI.TOTL|NY.GDP.MKTP.KD.ZG|MS.MIL.XPND.GD.ZS|SE.PRM.AGES|DT.DOD.DSTC.ZS|SP.POP....
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Data 621 - Homework #2
Overview In this homework assignment, you will work through various classification metrics. You will be asked to create functions in R to carry out the various calculations. You will also investigate some functions in packages that will let you obtain the equivalent results. Finally, you will create graphical output that also can be used to evalu...
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HW 1 Rough Draft
In this data set we are trying to identify good and bad teams in major league baseball team’s season. We are assuming some of the predictors will be higher for good teams. We will try to predict how many times a team will win in this season. DATA EXPLORATION: We can observe the response variable (TARGET_WINS) looks to be normally distributed. ...
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Publish Document
library(dplyr) library(Metrics) library(MLmetrics) library(leaps) library(car) library(MASS) library(tidyverse) library(caret) library(leaps) Load the Data train_raw <-read.csv("https://raw.githubusercontent.com/akarimhammoud/Data_621/main/Assignment_1/data/moneyball-training-data.csv") evaluation_raw <-read.csv("https://raw.githubusercontent....
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HW 1 - Model Selection
library(dplyr) library(Metrics) library(MLmetrics) library(leaps) library(car) Load Data Clean data # Review NA counts colSums(is.na(data)) ## INDEX TARGET_WINS TEAM_BATTING_H TEAM_BATTING_2B ## 0 0 0 0 ## TEAM_BATTING_3B TEAM_BATTING_HR TEAM_BATTING_BB TEAM_BA...
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Data 621 - Homework #4 Data Cleaning DRAFT
library(tidyverse) library(ggplot2) library(mice) library(car) library(Hmisc) library(corrplot) library(pscl) library(boot) library(nlme) Load data # Load insurance csv df_ins_raw <- read.csv("insurance_training_data.csv") # Removing index as instructed df_ins_raw <- subset(df_ins_raw, select = -c(INDEX)) # Preview data glimpse(df_ins_raw) ## ...
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