Publications by Ozili Nwokobia
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CAPSTONE PROJECT # Load libraries library(data.table) ## Warning: package 'data.table' was built under R version 4.3.3 library(ggplot2) library(xgboost) ## Warning: package 'xgboost' was built under R version 4.3.3 library(caret) ## Loading required package: lattice library(dplyr) ## ## Attaching package: 'dplyr' ## The following object is mask...
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Cancer Capstone Project
We are developing models that predict disease progression in patients using electronic health record data. It focuses on creating impactful solutions in healthcare by analyzing patient trends and identifying potential high-risk cases. First we are loading all the packages needed to visualize and understand the data using R. library(ggplot2) li...
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WORKSHOP III
IMPORTING THE DATASET AND CHANGING THE COLUM NAMES TO HELP WITH CORRELATION MATRIX EVP <- read.csv("C:/Users/Ozili Nwokobia/Downloads/Electric_Vehicle_Population_Data.csv", header=FALSE, stringsAsFactors=TRUE) View(EVP) str(EVP) ## 'data.frame': 181459 obs. of 17 variables: ## $ V1 : Factor w/ 11061 levels "1C4JJXN60P","1C4JJXN61P",..: 738...
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Workshop I & II
The data set selected for this work shop was the population of electric vehicles in Washington State EVP <- read.csv("C:/Users/Ozili Nwokobia/Downloads/Electric_Vehicle_Population_Data.csv", header=FALSE, stringsAsFactors=TRUE) View(EVP) Question 1: Will battery electric vehicles be more popular compared to hybrid plug-in because fully electric ...
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Project 4: Part 1
HAB <- read.csv("C:/Users/Ozili Nwokobia/OneDrive/Desktop/Health_AnimalBites.csv", stringsAsFactors=TRUE) View(HAB) str(HAB) ## 'data.frame': 9003 obs. of 15 variables: ## $ bite_date : Factor w/ 2703 levels "","1952-05-28 00:00:00",..: 4 5 6 7 8 9 10 11 12 13 ... ## $ SpeciesIDDesc : Factor w/ 10 levels "","BAT","CAT",..: 4 4 4...
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Accident Prediction
train<- data.frame(ClaimID = c(1,2,3), RearEnd = c(TRUE, FALSE, TRUE), Fraud = c(TRUE, FALSE, TRUE)) train ## ClaimID RearEnd Fraud ## 1 1 TRUE TRUE ## 2 2 FALSE FALSE ## 3 3 TRUE TRUE library(rpart) ## Warning: package 'rpart' was built under R version 4.3.3 mytree<-rpart(Frau...
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Comparing Learning Models
library(mlbench) library(caret) ## Loading required package: ggplot2 ## Loading required package: lattice data("PimaIndiansDiabetes") View(PimaIndiansDiabetes) trainControlI<-trainControl(method="repeatedcv", number=10, repeats=3) set.seed(7) fit.cart<-train(diabetes~., data = PimaIndiansDiabetes, method= "rpart", trControl=trainControlI) set...
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Naive Bayes Practice
library(caret) ## Loading required package: ggplot2 ## Loading required package: lattice library(klaR) ## Warning: package 'klaR' was built under R version 4.3.3 ## Loading required package: MASS data(iris) trainIndex<-createDataPartition(iris$Species, p=0.80, list = FALSE) dataTrain<-iris[trainIndex,] dataTest<-iris[-trainIndex,] fit<-NaiveBay...
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Project 3
Import the Titanic Data Set. T3 <- read.csv("C:/Users/Ozili Nwokobia/OneDrive/Desktop/PROJECT DATASET.txt") View(T3) str(T3) ## 'data.frame': 1309 obs. of 14 variables: ## $ pclass : chr "1st" "1st" "1st" "1st" ... ## $ survived : int 1 1 0 0 0 1 1 0 1 0 ... ## $ name : chr "Allen, Miss. Elisabeth Walton" "Allison, Master. Huds...
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R Part Practice
R Markdown train<- data.frame(ClaimID = c(1,2,3), RearEnd = c(TRUE, FALSE, TRUE), Fraud = c(TRUE, FALSE, TRUE)) train ## ClaimID RearEnd Fraud ## 1 1 TRUE TRUE ## 2 2 FALSE FALSE ## 3 3 TRUE TRUE library(rpart) ## Warning: package 'rpart' was built under R version 4.3.3 mytree<...
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