1. [k Nearest Neighbors] Consider properties of k-NN models: a. (2 pts) Suppose that we are...
Fantastic news! We've Found the answer you've been seeking!
Question:
Transcribed Image Text:
1. [k Nearest Neighbors] Consider properties of k-NN models: a. (2 pts) Suppose that we are using k-NN with just two training points, which have different (binary) labels. Assuming we are using k 1 and Euclidean distance, what = is the decision boundary? Include a drawing with a brief explanation. = b. (2 pts) For binary classification, given infinite data points, can k-NN with k 1 express any decision boundary? If yes, describe the (infinite) dataset you would use to realize a given classification decision boundary. If no, give an example of a decision boundary that cannot be achieved. c. (2 pts) Suppose we take k → ∞; what is the resulting model family? d. (2 pts) What effect does increasing the number of nearest neighbors k have on the bias-variance tradeoff? Explain your answer. [Hint: Use parts (b) and (c) in your explanation.] e. (2 pts) In logistic regression, we learned that we can tune the threshold of the linear classifier to trade off the true negative rate and the true positive rate. Explain how we can do so for k-NNs for binary classification. [Hint: By default, k-NN uses majority vote to aggregate labels of the k nearest neighbors; consider another option.] 1. [k Nearest Neighbors] Consider properties of k-NN models: a. (2 pts) Suppose that we are using k-NN with just two training points, which have different (binary) labels. Assuming we are using k 1 and Euclidean distance, what = is the decision boundary? Include a drawing with a brief explanation. = b. (2 pts) For binary classification, given infinite data points, can k-NN with k 1 express any decision boundary? If yes, describe the (infinite) dataset you would use to realize a given classification decision boundary. If no, give an example of a decision boundary that cannot be achieved. c. (2 pts) Suppose we take k → ∞; what is the resulting model family? d. (2 pts) What effect does increasing the number of nearest neighbors k have on the bias-variance tradeoff? Explain your answer. [Hint: Use parts (b) and (c) in your explanation.] e. (2 pts) In logistic regression, we learned that we can tune the threshold of the linear classifier to trade off the true negative rate and the true positive rate. Explain how we can do so for k-NNs for binary classification. [Hint: By default, k-NN uses majority vote to aggregate labels of the k nearest neighbors; consider another option.]
Expert Answer:
Answer rating: 100% (QA)
SOLUTION Sure Id be happy to help Here are the answers to the questions a 2 pts Suppose we have two training points x1 and x2 with different binary labels y1 and y2 We want to use kNN with k1 and Eucl... View the full answer
Related Book For
Introduction to Data Mining
ISBN: 978-0321321367
1st edition
Authors: Pang Ning Tan, Michael Steinbach, Vipin Kumar
Posted Date:
Students also viewed these programming questions
-
Case Study: Quick Fix Dental Practice Technology requirements Application must be built using Visual Studio 2019 or Visual Studio 2017, professional or enterprise. The community edition is not...
-
How many graphs will the following code create? import matplotlib.pyplot as plt plt . hist ( [ 1 , 2 , 3 ] ) plt . hist ( [ 1 , 2 , 3 ] ) plt . show ( ) Group of answer choices 3 1 0 2
-
The number of letter misprints per page of a book, where 24 pages have been taken at random from this book, is given below. Draw and appropriate control chart and provide interpretation. Page 1 2...
-
In an orbiting space vehicle, you are handed two identical boxes, one filled with sand and the other filled with feathers. How can you determine which is which without opening the boxes?
-
Quo Vadis Ltd would like to purchase additional non-current assets that cost R100 000 and is considering borrowing R100 000 from Ratios Ltd at 10% per annum to finance this. (Ignore taxation and...
-
Construct a Gantt chart for the general multipurpose plant in Figure 22.14, but with the unit assignments specified in Figure 22.13. Figure 22.13:- Figure 22.14:- Product A Product B Task 1 Task 2...
-
The balance in the unearned fees account, before adjustment at the end of the year, is $96,000. Of these fees, $78,500 have been earned. In addition, $23,600 of fees have been earned but have not...
-
(15 Points) Construct the minimized DFA equivalent to the following DFA. 2 1 3 0,1 1 0 1 4 1 1 5 6 0 0,1 0
-
Based on the attached case details address the following in at least 1. External environment (threats and opportunities) 2. Internal capabilities 3. Recommended business-level strategy to follow Case...
-
Assume that the (daily) demand (measured in hours of work) of unskilled labor in a particular town is given by D ( w ) = 150 10 w , where w denotes the hourly wage rate. The supply of unskilled labor...
-
Katherine Green is single with $ 164, 0 0 0 in gross income from her job at the Caitlin Bank. During the year she had $ 4 , 800 in adjustments. She had $ 2 3 , 0 0 0 in eligible 7 . 5 % medical...
-
How do resilient leaders cultivate emotional resilience, cognitive flexibility, and stress coping mechanisms to navigate adversity, setback, and failure in high-pressure environments, fostering a...
-
What discount rate would ensure a sustainable harvest is set to Maximum Sustainable Yield?
-
The following numbers give the weights of 22 students of a class. 42 32 75 50 80 60 51 44 47 39 56 44 66 70 80 40 55 36 38 67 65 53 38 41 72 64 50 45 33 64 58 46 38 41 73 47 63 37 43 59 71 79 35 52...
-
Kiddie Corp. uses a plantwide predetermined overhead rate based on machine - hours. The estimated costs for this rate were total fixed manufacturing overhead cost of $ 1 14 , 0 0 0 , variable...
-
B:- The bore and stroke of an internal combustion engine working on Otto cycle are (17 cm) and (30 cm) respectively. If the total volume is (8.825 cm),find the air standard efficiency. Take X=1.4
-
As economic conditions change, how do banks adjust their asset portfolio?
-
You are asked to evaluate the performance of two classification models, M1 and M2. The test set you have chosen contains 26 binary attributes, labeled as A through Z. Table 5.5 shows the posterior...
-
Construct a data cube from Table 3.1. Is this a dense or sparse data cube? If it is sparse, identify the cells that are empty. Table 3.1 Product ID Location ID|Number Sold 10 6
-
We can represent a data set as a collection of object nodes and a collection of attribute nodes, where there is a link between each object and each attribute, and where the weight of that link is the...
-
What are a manager's resources?
-
What are the three levels of management?
-
Joe Maddon has been the manager of the Chicago Cubs since 2015. In his first year, he exceeded the expectations of most analysts and fans by leading the team to an appearance in the National League...
Study smarter with the SolutionInn App