Georgia Institute of Technology

ISyE7406 – HOMEWORK 4 Spring 2023 1. Introduction In this homework, we will examine how various local smoothing methods estimate the “Mexican hat function” at various points in the interval [-2π, 2π]. Using these methods, we will be able to better understand how bias, variance, and mean square error of these estimators perform given different spans, bandwidths, and local smoothing parameters. 2. Exploratory Data Analysis The Mexican hat function is defined in the range [-2π, 2π...

Introduction Work with “fat” data set and apply 7 linear regression models to the data set. For each model, find out the testing error. Since the data set is small, apply Monte Carlo Cross Validation to all the models and find out the average Testing error for each model after 100 loops. Exploratory Data Analysis The “fat” data set has 252 observations and 18 variables. The first column “brozek” is the dependent variable representing the percentage of body fat. The rest 17 vari...

Quiz #4 Due Apr 9 at 10:59pm Points 5 Questions 10 Available Mar 31 at 7am - Apr 9 at 10:59pm Time Limit 40 Minutes Instructions This quiz was locked Apr 9 at 10:59pm. Attempt History Attempt Time Score LATEST Attempt 1 11 minutes 4.5 out of 5 Score for this quiz: 4.5 out of 5 Submitted Apr 9 at 7:36pm This attempt took 11 minutes. Warning: this is the real quiz #4 that counts 5% of your final course grade. You can take this quiz once and only once! In particular, once you start the ...

PLS Regression? The choice of k depends on the application and can be chosen by the cross validation Correct! The choice of k should be as large as possible, say, k=p. The choice of k should be a small number such as k=2,3 or 5. Question 2 1 / 1 pts In the linear regression model , the Laplace Prior on yields the estimator of the form LASSO Correct! Ridge regression None of the above Question 3 1 / 1 pts What is the main difference between linear discriminant analysis (LDA) and Log...

Quiz #3 Due Feb 26 at 10:59pm Points 5 Questions 5 Available Feb 10 at 7am - Feb 26 at 10:59pm Time Limit 40 Minutes Instructions This quiz was locked Feb 26 at 10:59pm. Attempt History Attempt Time Score LATEST Attempt 1 34 minutes 3 out of 5 Score for this quiz: 3 out of 5 Submitted Feb 26 at 10:48pm This attempt took 34 minutes. Warning: this is the real quiz #3 that counts 5% of your final course grade. You can take this quiz once and only once! In particular, once you start the ...

Quiz #1 Due Jan 29 at 10:59pm Points 5 Questions 5 Available Jan 13 at 7am - Jan 29 at 10:59pm Time Limit 40 Minutes Instructions This quiz was locked Jan 29 at 10:59pm. Attempt History Attempt Time Score LATEST Attempt 1 30 minutes 5 out of 5 Score for this quiz: 5 out of 5 Submitted Jan 29 at 10:39pm This attempt took 30 minutes. Warning: this is the real quiz that counts 5% of your final course grade. You can take this quiz once and only once! In particular, once you start the qui...

ISyE7406 – HOMEWORK 4 Spring 2023 1. Introduction In this homework, we will examine how various local smoothing methods estimate the “Mexican hat function” at various points in the interval [-2π, 2π]. Using these methods, we will be able to better understand how bias, variance, and mean square error of these estimators perform given different spans, bandwidths, and local smoothing parameters. 2. Exploratory Data Analysis The Mexican hat function is defined in the range [-2π, 2π...

ISYE 7404 2 Introduction The objective of this assignment is to study how well three distinct local smoothing techniques (LOESS, Nadaraya-Watson (NW) kernel smoothing, and Spline Smoothing) perform on a simulated additive noise model. �� = �(�) + ��, Consuming the Mexican Hat function �(�) = (1 − �2 ) exp(−0.5�2 ), where � � [-2�, 2�]. In the additive noise model, the error terms follow a normal distribution with mean 0 and standard deviation 0.2, and ar...

HW2 Introduction Work with “fat” data set and apply 7 linear regression models to the data set. For each model, find out the testing error. Since the data set is small, apply Monte Carlo Cross Validation to all the models and find out the average Testing error for each model after 100 loops. Exploratory Data Analysis The “fat” data set has 252 observations and 18 variables. The first column “brozek” is the dependent variable representing the percentage of body fat. The rest 17...

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