Title | Homework week #2. Task 3.1(a). Use the ksvm or kknn function to find a good classifier using cross-validation. |
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Course | Intro to Analytics Modeling |
Institution | Georgia Institute of Technology |
Pages | 2 |
File Size | 59.7 KB |
File Type | |
Total Downloads | 62 |
Total Views | 129 |
Using the same data set (credit_card_data.txt or credit_card_data-headers.txt) as in Question 2.2, use the ksvm or kknn function to find a good classifier, (a) using cross-validation (do this for the k-nearest-neighbors model; SVM is optional); (K-Fold CV)....
HW2_3.1 a
HW2. Q3_1_a Part I: Load libraries, set the wd, set the seed, etc. rm(list = ls()) library(kknn) #install.packages("plotly") library(plotly) ## Loading required package: ggplot2 ## ## Attaching package: ’plotly’ ## The following object is masked from ’package:ggplot2’: ## ## last_plot ## The following object is masked from ’package:stats’: ## ## filter ## The following object is masked from ’package:graphics’: ## ## layout library(glue) set.seed(31) cc_data...