Publications by Ramon Rodriguez-Santana, MBA,MPH
Time series forecasting using {modeltime} in R
Create Forecasting Models by Combining {modeltime} and {parsnip} Packages Here are the instructions on how to perform classical time series analysis and machine learning modeling in one framework. Set working directory where dataset is located. setwd("~/Documents/Time Series Forecasting Using ML Models in R") Load libraries. library(modeltime) ...
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Model deployment using {plumber} package in R
This presentation shows the steps on how to deploy a GLM (Logistic Regression) machine learning model created in R via a Plumber API. FIRST: Create ‘1_ML_Model_Train.R’ file Setup working directory. setwd("~/Documents/Deploying a simple ML model with Plumber 101") Load libraries. library(tidyverse) ## ── Attaching core tidyverse packag...
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Compare 13 models and select the best using the {caret} R package
Compare the estimated accuracy of different machine learning algorithms (models). Select the most accurate model for your predictive analytics project. When working on a machine learning project, you often have several good models to choose from. Each of the models you selected needs to be measure for accuracy. In order to select the best and final...
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Using {Rayshaders} package to visualize 3D map in R
What is the {Rayshaders} package? “rayshader is an open source package for producing 2D and 3D data visualizations in R. rayshader uses elevation data in a base R matrix and a combination of raytracing, hillshading algorithms, and overlays to generate stunning 2D and 3D maps. In addition to maps, rayshader also allows the user to translate ggplot...
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Using the AutoML {forester} package for Tree-based Models
What is the {forester} AutoML package? The forester is an AutoML tool in R for tabular data regression and binary classification tasks. It wraps up all machine learning processes into a single train() function, which includes: i) rendering a brief data check report, ii) preprocessing the initial dataset enough for models to be trained, iii) trainin...
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Spatial statistical modeling and prediction using the {spmodel} package in R
Spatial statistical modeling and prediction using {spmodel} Here is some information regarding the {spmodel} package. “spmodel is an R package used to fit, summarize, and predict for a variety spatial statistical models applied to point-referenced or areal (lattice) data. Parameters are estimated using various methods, including likelihood-based ...
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Using the {sociome} package to identify high deprivation areas in Connecticut.
What is the Area Deprivation Index (ADI)? “The Area Deprivation Index (ADI) is based on a measure created by the Health Resources & Services Administration (HRSA) over two decades ago for primarily county-level use, but refined, adapted, and validated to the Census block group/neighborhood level by Amy Kind, MD, PhD and her research team at the U...
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Exploring data using the vtree package
Using the vtree package The {vtree} package is a tool for calculating and displaying variable trees. Here are the steps on how to use the vtree package. Set working directory. # Set working directory setwd("C:/MyRData/Exploring data using the vtree package") Upload libraries. Always include the {tidyverse} package. # Upload tidyverse library...
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Using sf package for spatial counting points in polygons via spatial join
Using sf package for spatial counting points in polygons… Here are the steps for spatial counting points (i.e., Long and Lat coordinates) using the {sf} package Note. To save the R code from this tutorial, please copy and paste to your RStudio the lines of code located in the gray boxes. Set working directory (i.e.,Working Folder). In this fo...
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Finding variable importance in a logistic regression model in R
Finding variable importance Here are the steps on how to assess variable importance in a logistic regression analysis. Set working directory/folder. setwd("C:/MyRData/Logistic Regression Model Variable Importance") Load package. library(tidyverse) ## -- Attaching packages --------------------------------------- tidyverse 1.3.2 -- ## v ggplot2...
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