Publications by Brett Stokes
CR Case Study
Train Test Split data("acquisitionRetention") acquisitionRetention$acquisition=as.factor(acquisitionRetention$acquisition) #anyNA(acquisitionRetention) index = sample(nrow(acquisitionRetention),0.8*nrow(acquisitionRetention)) train = acquisitionRetention[index,] test= acquisitionRetention[-index,] Logistic Regression model <- glm(acquisitio...
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Homework 1
Exercise 1: ACF and PACF from simulated data under ARMA(p,q) model For simulated stationary data (n=200) under different ARMA models listed below, (i) plot observations, (ii) plot its ACF and PACF plots, and (iii) describe what you observe from ACF and PACF. a) Two sets of simulated stationary data under AR(3) model by specifying coefficients (�...
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Homework 2
Exercise 1: Seasonal ARIMA Use the “Electricity.RData” examined in HW1 Exercise 2 (d)-(f). Fit the model using first order differenced log transformed series. (a) By visually checking, decide what SARIMA models seem appropriate, i.e., specify p, d, q and P,D,Q in SARIMA model, ARIMA(p, d, q) ∗ ARIMA(P,D, Q)𝑠. Choose the most appropriate ...
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Assignment 8
Chapter 09 (page 368): 5, 7, 8 Problem 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. Generate a dat...
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Assignment 6
Problem 6 In this exercise, you will further analyze the Wage data set considered throughout this chapter (a) Perform polynomial regression to predict wage using age. Use cross-validation to select the optimal degree d for the polynomial. What degree was chosen, and how does this compare to the results of hypothesis testing using ANOVA? Make a pl...
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Assignment 7
Problem 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, and ent...
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