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Introduction to data mining 课后答案 169页

Data

Mining

Data

Science

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Introduction to data mining from Pang-Ning Tan the first edition. This book is only the answers of the questions in every chapter

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Introduction to Data Mining

Instructor’s Solution Manual

Pang-Ning Tan

Michael Steinbach

Vipin Kumar

Contents

1 Introduction 1

2Data 5

3 Exploring Data 19

4 Classiﬁcation: Basic Concepts, Decision Trees, and Model

Evaluation 25

5 Classiﬁcation: Alternative Techniques 45

6 Association Analysis: Basic Concepts and Algorithms 71

7 Association Analysis: Advanced Concepts 95

8 Cluster Analysis: Basic Concepts and Algorithms 125

9 Cluster Analysis: Additional Issues and Algorithms 147

10 Anomaly Detection 157

iii

Introduction

1. Discuss whether or not each of the following activities is a data mining

task.

(a) Dividing the customers of a company according to their gender.

No. This is a simple database query.

(b) Dividing the customers of a company according to their prof-

itability.

No. This is an accounting calculation, followed by the applica-

tion of a threshold. However, predicting the proﬁtability of a new

customer would be data mining.

No. Again, this is simple accounting.

(d) Sorting a student database based on student identiﬁcation num-

bers.

No. Again, this is a simple database query.

(e) Predicting the outcomes of tossing a (fair) pair of dice.

No. Since the die is fair, this is a probability calculation. If the

die were not fair, and we needed to estimate the probabilities of

each outcome from the data, then this is more like the problems

considered by data mining. However, in this speciﬁc case, solu-

tions to this problem were developed by mathematicians a long

time ago, and thus, we wouldn’t consider it to be data mining.

(f) Predicting the future stock price of a company using historical

records.

Yes. We would attempt to create a model that can predict the

continuous value of the stock price. This is an example of the

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