Publications by IvanTikhonov
Data698 Final Research Project
#Abstract: Given the alarming global child mortality rate, this project focused on two main objectives: 1) identifying countries with the highest and lowest child mortality rates and 2) developing a precise predictive model to understand the factors influencing child mortality and identify variables that can help reduce this rate. The methodolo...
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DATA608 FinalProject
#Intoduction I am creating a visualization for my final project that highlights the global nursing shortage and its impact on healthcare systems worldwide. The nursing shortage has been declared a “global health emergency,” and it has worsened due to the COVID-19 pandemic. To ensure the reliability and relevance of the data, I will be using...
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DATA621 Insurance Quotes
Abstract We discuss the challenges from evaluating insurance data, asserting whether a car is involved in a crash and then how expensive the claim would be. Mainly, we discuss imputation but our end models are not able to effectively predict car crashes due to overfitting and high false positives. Our linear regression models pull some insights...
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DATA609 Module 7
Ex.1 Use the svm() algorithm of the e1071 package to carry out the support vector machine for the PlantGrowth data set. Then, discuss the number of support vectors/samples. Install the e1071 package in R if needed. library(e1071) plant_svm <- svm(group ~ ., data = PlantGrowth) summary(plant_svm) ## ## Call: ## svm(formula = group ~ ., data =...
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DATA609 Module 6
Ex.1 Use a data set such as the PlantGrowth in R to calculate three different distance metrics and discuss the results. plants_euclidean <- dist(PlantGrowth, method = "euclidean") ## Warning in dist(PlantGrowth, method = "euclidean"): NAs introduced by coercion as.matrix(plants_euclidean) ## 1 2 3 4 5...
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DATA609 Module 5
Ex. 1 Carry out the logistic regression (Example 22 on Page 94) in R using the data x 0.1 0.5 1.0 1.5 2.0 2.5 y 0 0 1 1 1 0 The formula is \[y(x) = \frac{1}{1 + exp[-(a + bx)]}\] I will use here glm function with family as binomial to perform logistic regression for given values of x and y. x <- c(0.1, 0.5, 1.0, 1.5, 2.0, 2.5) y <- c(0, 0, 1, 1...
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DATA608 Module 4
library(ggplot2) library(ggrepel) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(dbplyr) ## ## Attaching package: 'dbplyr' ## The following object...
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DATA621 HW 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 ev...
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DATA621 HW 2
library(tidyverse) ## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ── ## ✔ ggplot2 3.4.1 ✔ purrr 1.0.1 ## ✔ tibble 3.1.8 ✔ dplyr 1.0.10 ## ✔ tidyr 1.3.0 ✔ stringr 1.5.0 ## ✔ readr 2.1.3 ...
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DATA 609 Module 4
Ex 1 For Example 19 on Page 79 in the book, carry out the regression using R. x -0.98 1.00 2.02 3.03 4.00 y 2.44 -1.51 -0.47 2.54 7.52 x <- c(-0.98, 1.00, 2.02, 3.03, 4.00) y <- c(2.44, -1.51, -0.47, 2.54, 7.52) model1 <- lm(y~x) model1 ## ## Call: ## lm(formula = y ~ x) ## ## Coefficients: ## (Intercept) x ## 0.4038 ...
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