Publications by Nikoleta Emanouilidi
Project 2 Data624
INSTRUCTIONS Hide Assignment Information Instructions Project #2 (Team) Assignment This is role playing. I am your new boss. I am in charge of production at ABC Beverage and you are a team of data scientists reporting to me. My leadership has told me that new regulations are requiring us to understand our manufacturing process, the predictive ...
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Homework 10 Data 624
Imagine 10000 receipts sitting on your table. Each receipt represents a transaction with items that were purchased. The receipt is a representation of stuff that went into a customer’s basket - and therefore ‘Market Basket Analysis’. That is exactly what the Groceries Data Set contains: a collection of receipts with each line representing...
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Homework 9 Data 624
8.1. Recreate the simulated data from Exercise 7.2: library(mlbench) ## Warning: package 'mlbench' was built under R version 4.3.3 set.seed(200) simulated <- mlbench.friedman1(200, sd = 1) simulated <- cbind(simulated$x, simulated$y) simulated <- as.data.frame(simulated) colnames(simulated)[ncol(simulated)] <- "y" (a) Fit a random forest mode...
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Homework 8 Data 624
library(ggplot2) library(RANN) library(magrittr) library(caret) ## Loading required package: lattice library(ggplot2) library(reshape2) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## inters...
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HW 7 Data 624
6.2. Developing a model to predict permeability (see Sect. 1.4) could save significant resources for a pharmaceutical company, while at the same time more rapidly identifying molecules that have a sufficient permeability to become a drug: (a) Start R and use these commands to load the data: library(caret) library(glmnet) library(AppliedPredic...
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Project 1 Data624
Part A – ATM Forecast In part A, I want you to 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 hundreds of dollars, other than that it is straight forward. I am being somewhat ambiguous on purpose to make this have a little more business ...
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Homework 6 Data 624
Question 1 Figure 9.32 shows the ACFs for 36 random numbers, 360 random numbers and 1,000 random numbers. a) Explain the differences among these figures. Do they all indicate that the data are white noise? The three ACF plots display white noise series of different lengths: 36, 360, and 1,000 numbers. In the plot with 36 numbers, there are s...
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Homework 5 Data 624
library(fpp3) library(fable) library(ggplot2) library(tsibble) library(dplyr) Question 1 Consider the the number of pigs slaughtered in Victoria, available in the aus_livestock dataset. a) Use the ETS() function to estimate the equivalent model for simple exponential smoothing. Find the optimal values of a and l0 , and generate forecasts ...
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Homework 4 Data 624
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.The data can be accessed via: library...
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Homework 3 Data 624
1 Produce forecasts for the following series using whichever of NAIVE(y), SNAIVE(y) or RW(y ~ drift()) is more appropriate in each case: Australian Population (global_economy) Bricks (aus_production) NSW Lambs (aus_livestock) Household wealth (hh_budget). Australian takeaway food turnover (aus_retail). library(fpp3) ## Warning: package 'fpp3...
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