Publications by Group 4
DATA605 Final Project
library(tidyverse) library(gridExtra) library(kableExtra) library(psych) library(corrplot) library(matrixcalc) library(MASS) library(Rmisc) library(mice) library(VIM) library(broom) Problem 1 Using R, generate a random variable X that has 10,000 random uniform numbers from 1 to N, where N can be any number of your choosing greater than...
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DATA605 Assignment 15
Question 1 Find the equation of the regression line for the given points. Round any final values to the nearest hundredth, if necessary. (5.6, 8.8), (6.3, 12.4), (7, 14.8), (7.7, 18.2), (8.4, 20.8) x <- c(5.6, 6.3, 7, 7.7, 8.4 ) y <- c(8.8, 12.4, 14.8, 18.2, 20.8) df <- data.frame(cbind(x, y)) xy.lm <- lm(y ~ x, data = df) xy.lm ## ## Call...
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DATA605 Assignment 14
Equation 1 \[\pmb{f(x) = \frac{1}{(1-x)}}\] Function evaluated at \(0\): \[f(0) = \frac{1}{1-0} = 1\] Function re-written: \[\frac{1}{(1-x)} = 1(1-x)^{-1}\] Derivatives First Derivative: \[f'(x) = -1(1-x)^{-2}.(-1)= 1(1-x)^{-2} = \frac{1}{(1-x)^{2}}\] First Derivative evaluated: \(f'(0) = 1\) Second Derivative: \[f''(x) = -2(1-x)^{-3}.(-1)= ...
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DATA624 Homework 4
3.1. The UC Irvine Machine Learning Repository6 contains a data set related to glass identification. The data consist of 214 glass samples labeled as one of seven class categories. There are nine predictors, including the refractive index and percentages of eight elements: Na, Mg, Al, Si, K, Ca, Ba, and Fe. library(mlbench) library(tidyverse) ...
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DATA621 - Blog 3: Automated EDA - DataExplorer
Before performing analysis or any type of predictive modeling on a data set, you may want to see what the data looks like in order to understand what problem solving techniques you can develop to derive the desired information you wish to obtain from the data. A lot of time, cleaning and organizing data can be time-consuming. There is an R packag...
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DATA624 Homework 6
library(tidyverse) library(fpp2) library(urca) 8.1 Figure 8.31 shows the ACFs for 36 random numbers, 360 random numbers and 1,000 random numbers. Explain the differences among these figures. Do they all indicate that the data are white noise? Time series data are considered white noise if less than 5% of the ACF spikes are above the 95% limi...
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DATA621 Project 1
library(fpp2) library(tidyverse) library(readxl) library(e1071) library(caret) library(car) library(kableExtra) library(GGally) library(gridExtra) library(mice) PART A: ATM FORECAST Forecast how much cash is taken out of 4 different ATM machines for May 2010. The data is given in a single file. The variable ‘Cash’ is provided in hun...
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DATA621 Final Project
Abstract The purpose of this paper is to provide researchers and readers a comprehensive review of scholarly research on credit risk analysis using various classification models to predict whether a customer may get approved for a loan based on the features of their background similar to what is in the dataset used. Credit risk is usually the res...
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DATA608 Module 6
DATA608 Module 6 Javern Wilson 4/11/2020 Assignment 6: D3 lab D3.js is a powerful data visualization library. Rather than being based around existing plot types, d3 allows you to bind any html element. This power is a double edged sword. It allows you to build completely custom data visualizations, but because you’re dealing with individual ...
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