Publications by Emily Bates
Tennis Project
####################################################################### ########################## TENNIS PROJECT ########################### ####################################################################### # Libraries library(MASS) ; library(ggplot2) ; library(scales) ; library(tidyverse) ; library(corrplot) ## ── Attaching core tid...
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Assignment 8
library(ISLR2) library(ggplot2) library(e1071) Question 5 We have seen that we can fit an SVM with a non-linear kernel in order to perform classification using a non-linear decision boundary. We will now see that we can also obtain a non-linear decision boundary by performing logistic regression using non-linear transformations of the features. (a...
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Assignment 7
library(ggplot2) library(ISLR2) library(tree) library(randomForest) ## randomForest 4.7-1.1 ## Type rfNews() to see new features/changes/bug fixes. ## ## Attaching package: 'randomForest' ## The following object is masked from 'package:ggplot2': ## ## margin #install.packages("BART") library(BART) ## Loading required package: nlme ## Loading ...
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Assignment 5
Question 2 For parts (a) through (c), indicate which of i. through iv. is correct. Justify your answer. (a) The lasso, relative to least squares, is: i. More flexible and hence will give improved prediction accuracy when its increase in bias is less than its decrease in variance. ii. More flexible and hence will give improved prediction accuracy wh...
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Assignment 4
Question 3 We now review k-fold cross-validation. (a) Explain how k-fold cross-validation is implemented. K-Fold Cross Validation is used to evaluate the performance of your predictive model. Previously we’ve learned about splitting our data into 1 train set and 1 test set. The K-Fold approach differs in that you divide your data into “k” equ...
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Assignment 3
Question 13 This question should be answered using the Weekly data set, which is part of the ISLR2 package. This data is similar in nature to the Smarket data from this chapter’s lab, except that it contains 1,089 weekly returns for 21 years, from the beginning of 1990 to the end of 2010. Produce some numerical and graphical summaries of the Wee...
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Assignment2
Question 2 Carefully explain the differences between the KNN classifier and KNN regression methods. KNN Classifier is used for classification tasks while KNN Regression is used for regression tasks. This means that KNN Classifier is used when the response variable is categorical, while KNN Regression is used when the response variable is a continu...
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