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Consider the following 3×3 checkerboard pattern. Suppose our goal is to perfectly classify the range shown such that all black regions are labeled as +1 and all white regions are labeled as –1 3 2 1 2 3 Figure 1: Checkerboard Pattern What is the minimum depth of decision tree that perfectly classifies the 3×3 colored regions in Figure 1, using features that only inspect either x or y but not both x and y? (How you use each of X and y to construct a feature is up to you.) What is the minimum depth of decision trees to perfectly classify the colored regions in Figure 1, using ANY features of x and y?

Consider the following 3×3 checkerboard pattern. Suppose our goal is to perfectly classify the range shown such that all black regions are labeled as +1 and all white regions are labeled as –1 3 2 1 2 3 Figure 1: Checkerboard Pattern What is the minimum depth of decision tree that perfectly classifies the 3×3 colored regions in Figure 1, using features that only inspect either x or y but not both x and y? (How you use each of X and y to construct a feature is up to you.) What is the minimum depth of decision trees to perfectly classify the colored regions in Figure 1, using ANY features of x and y?

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Consider the following 3×3 checkerboard pattern. Suppose our goal is to perfectly classify the range shown such that all black regions are labeled as +1 and all white regions are labeled as –1 3 1 1 2 3 Figure 1: Checkerboard Pattern What is the minimum depth of decision tree that perfectly classifies the 3×3 colored regions in Figure 1, using features that only inspect either x or y but not both x and y? (How you use each of X and y to construct a feature is up to you.) What is the minimum depth of decision trees to perfectly classify the colored regions in Figure 1, using ANY features of x and y?
Transcribed Image Text:Consider the following 3×3 checkerboard pattern. Suppose our goal is to perfectly classify the range shown such that all black regions are labeled as +1 and all white regions are labeled as –1 3 1 1 2 3 Figure 1: Checkerboard Pattern What is the minimum depth of decision tree that perfectly classifies the 3×3 colored regions in Figure 1, using features that only inspect either x or y but not both x and y? (How you use each of X and y to construct a feature is up to you.) What is the minimum depth of decision trees to perfectly classify the colored regions in Figure 1, using ANY features of x and y?
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