We are intrested in predicting the percentage of people commuting to work by walking given some input variables. Each observation corresponds to a different city and each input variable summarizes some characteristic of a given city, such as density, urban sprawl and average income per capita. This is 1.not a machine learning problem. Only social scientists would be interested in such a problem. 2.both a classification and a regression problem as it depends on the way one codes the output variable as either 0, 1 or a a particular number in the [0,1] interval. 3.a regression problem. The output variable is continuous. 4.a classification problem. Walking to work is a discrete variable and can only take two values: to walk to work and not to walk to wor

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Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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We are intrested in predicting the percentage of people commuting to work by walking given some input variables. Each observation corresponds to a different city and each input variable summarizes some characteristic of a given city, such as density, urban sprawl and average income per capita. This is

	1.	not a machine learning problem. Only social scientists would be interested in such a problem.
	2.	both a classification and a regression problem as it depends on the way one codes the output variable as either 0, 1 or a a particular number in the [0,1] interval.
	3.	a regression problem. The output variable is continuous.
	4.	a classification problem. Walking to work is a discrete variable and can only take two values: to walk to work and not to walk to wor

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