Publications by Victor Feagins
R Basics: intro to Dataframes HW
Instructions This assignment you will be practicing working with dataframes in R. Reading in data calculating simple statistics. We will be working with the education_data.csv file we saw in class. This file are records of students test scores in the fall and spring semesters in one academic school year. Exercise Create a R script to record all...
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Assignment #1 Data Mining
Conceptual Questions Question 2 Explain whether each scenario is a classification or regression problem, and indicate whether we are most interested in inference or prediction. Finally, provide n and p. We collect a set of data on the top 500 firms in the US. For each firm we record profit, number of employees, industry and the CEO salary. We ...
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HW 1
Victor Feagins victorfeagins@att.net Use a screen capture tool to take a capture of you R session showing version 4.0.3 myimage Use a screen capture tool to take a capture of you QGIS session showing version 3.16.3 myimage ...
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Homework 4 GIS for Population Science
Load Libraries library(tidycensus) library(tidyverse) ## -- Attaching packages --------------------------------------------------------------------------------------------------------------- tidyverse 1.3.0 -- ## v ggplot2 3.3.3 v purrr 0.3.4 ## v tibble 3.0.3 v dplyr 1.0.3 ## v tidyr 1.1.2 v stringr 1.4.0 ## v readr 1.3....
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Data Mining HW # 2
Question 2 Carefully explain the differences between the KNN classifier and KNN regression methods. Both KNN classifier and KNN regression is a non parametric approach to model data. Both depend on parameter k which is the number of nearest neighbors that the algorithm will look for to estimate the value of the response. The classifier method lo...
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Simple Parallel Presentation
Simple ParallelVictor Feagins3/2/2021 Starting and stopping clusters library(parallel) detectCores() #How many cores do you have [1] 8 cl <- makeCluster(2) #starting a cluster #cl <- makeForkCluster(8) #fork clusters don't work on windows #stopCluster(cl) #Stopping cluster Sending libraries to Clusters clusterEvalQ(cl, { library(tidyverse...
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Geocoding HW 5 GIS for Population Science
Packages library(censusxy) ## Warning: package 'censusxy' was built under R version 4.0.4 library(tmap) library(sf) library(tidyverse) library(readxl) Read in Data wic <- read_excel("Data/wic_west_side.xls") ## New names: ## * Source -> Source...1 ## * Source -> Source...223 grocery <- read_excel("Data/grocery_west_side.xls") ## New names: ...
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Data Mining HW 3
The following are my answers to questions 10,11,13 in Chapter 4 of the ISLR book library(ISLR) library(tidyverse) ## -- Attaching packages --------------------------------------- tidyverse 1.3.0 -- ## v ggplot2 3.3.3 v purrr 0.3.4 ## v tibble 3.1.0 v dplyr 1.0.3 ## v tidyr 1.1.3 v stringr 1.4.0 ## v readr 1.4.0 v forc...
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HW 6 Point Pattern Analysis Lab
Packages library(sf) ## Warning: package 'sf' was built under R version 4.0.4 ## Linking to GEOS 3.9.0, GDAL 3.2.1, PROJ 7.2.1 library(tidyverse) ## -- Attaching packages --------------------------------------- tidyverse 1.3.0 -- ## v ggplot2 3.3.3 v purrr 0.3.4 ## v tibble 3.1.0 v dplyr 1.0.5 ## v tidyr 1.1.3 v stringr 1.4.0...
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HW 3 Data Mining Resampling Methods
Question 3. Explain how k-fold cross-validation is implemented. K fold cross validation is implemented as a way to validate a model. How it is implemented is by dividing the data set into k combinations testing and training sets of data. Then taking the average of the errors of all K combinations. This means that the model was tested and traine...
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