Publications by Jose Rodriguez
Assignment 8
library(e1071) library(ggplot2) library(ISLR2) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union We have seen that we can fit an SVM with a non-linear kernel in orde...
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Assignment 7
Assignment 7 3. Consider the Gini index, classification error, and entropy in a simple classification setting with two classes. Create a single plot that displays each of these quantities as a function of ˆpm1. The x-axis should display ˆpm1, ranging from 0 to 1, and the y-axis should display the value of the Gini index, classification error, an...
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Assignment 6
library(ISLR2) library(boot) library(caret) ## Loading required package: ggplot2 ## Loading required package: lattice ## ## Attaching package: 'lattice' ## The following object is masked from 'package:boot': ## ## melanoma library(leaps) library(gam) ## Loading required package: splines ## Loading required package: foreach ## Loaded gam 1.22-...
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Assignment5
Chapter 06 (page 259): 2, 9, 11 library(MASS) library(glmnet) ## Loading required package: Matrix ## Loaded glmnet 4.1-6 library(ISLR2) ## ## Attaching package: 'ISLR2' ## The following object is masked from 'package:MASS': ## ## Boston library(pls) ## ## Attaching package: 'pls' ## The following object is masked from 'package:stats': ## ##...
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Assignment 4
library(ISLR2) #3 We now review k-fold cross-validation. (a) Explain how k-fold cross-validation is implemented. By dividing the data set into k different and equal subsets, we can choose one set k1 of length 1/k ,set it apart, and fit the method in the remaining k-1 sets. The MSE is the used in the held out set (k1). By repeating this process, alt...
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Assignment 3
Chapter 04 (page 168): 13, 14, 16 library(ISLR2) library(MASS) ## ## Attaching package: 'MASS' ## The following object is masked from 'package:ISLR2': ## ## Boston library(class) library(e1071) library(caTools) 13. This question should be answered using the Weekly data set, which is part of the ISLR2 package. This data is similar in nature t...
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Data Mining - Assignment 2
Q2 Carefully explain the differences between the KNN classifier and KNN regression methods. KNN classifier and KNN regression methods are non-parametric approaches that depend on the value of a k-number of neighbors of a point to define the value of that point. The difference between both methods resides in the fact that a KNN classifier assigns t...
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