Publications by Darwhin Gomez
Project2: Predict PH
ABC Beverage Company Introduction and Abstract In response to new regulations requiring ABC Beverage to better understand our manufacturing process and predictive factors for PH levels, our data science team analyzed historical production data to build a reliable forecasting model. The goal was to identify the key factors influencing PH and cre...
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Groceries
Instructions 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...
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Data 624 Assignment 9
8.1 A 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" model1 <- randomForest(y ~ ., data = simulated, importance = TRUE, ntree = 1000) rfImp1 <- varImp(model1...
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Assignment 8
7.2. ## Friedman (1991) introduced several benchmark data sets create by sim ulation. One of these simulations used the following nonlinear equation to create data: y =10sin(πx1x2) +20(x3 −0.5)2 +10x4 +5x5 +N(0,σ2) where the x values are random variables uniformly distributed between [0, 1] (there are also 5 other non-informative variables a...
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Data 607 lab7
Web Scraping Overview This is a two part assignment. In the first part of the assignment you will practice rectangling on a dataset from the repurrrsive package. In the second part you will combine the rvest package along with functions and iteration to scrape data on foreign linked political action committees from the website open secrets. li...
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Assignment 7
library(ggplot2) library(caret) library(dplyr) library(pls) library(RANN) library(MASS) library(lars) library(randomForest) library(elasticnet) library(ggcorrplot) library(tidyr) library(reshape2) set.seed(895) theme_set(theme_bw()) 6.2. Developing a model to predict permeability (see Sect. 1.4) could save significant resources for a...
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Data 624 Project 1
Part A Data Acquisition & Data Processing The data has been loaded. I need to convert the date column to a date-type variable. Next, I will transform the atm_data data frame into a tsibble. I will also rename some of the variables to make them more descriptive. atm_data <- read_excel("ATM624Data.xlsx", col_types = c("date", "text", "numeric"))...
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Data 624 Assignment 6
ARIMA Modeling: Instructions Do the exercises 9.1, 9.2, 9.3, 9.5, 9.6, 9.7, 9.8 in Hyndman. Please submit both the Rpubs link as well as your .rmd file. 9.1 A. Explain the differences among these figures. Do they all indicate that the data are white noise? As we examine the graphs, we see that the spikes in the lags diminish as n (the length ...
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Data 607
Lab 5: Working with Text and Strings Author Darwhin Gomez Overview In this lab you will practice perform a series of exercises that use text and string manipulation to either analyze data with text, manipulate data containing strings, apply regular expressions, or handle data files with unusual formats or text strings. Problems Problem 1. Usin...
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Assignment 5
library(fpp3) ## Warning: package 'fpp3' was built under R version 4.4.1 ## Registered S3 method overwritten by 'tsibble': ## method from ## as_tibble.grouped_df dplyr ## ── Attaching packages ────────────────────────────────────────────...
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