## Data Mining Concepts and Techniques ? Chapter 10. Part 2

### Data Mining Concepts and Techniques TUT

Data Mining Concepts and Techniques TUT. 4. CHAPTER 1. INTRODUCTION (d) Describe the steps involved in data mining when viewed as a process of knowledge discovery. The steps involved in data mining when viewed as a process of knowledge, Data Mining Concepts and Techniques, Third Edition by Jiawei Han, Micheline Kamber, Jian Pei (Solution Manual) ISBN-13: 978-0123814791 ISBN-10: 0123814790 Instant Access After Placing The Order. All The Chapters Are Included..

### Data Mining Concepts and Techniques ? Chapter 10. Part 2

Data Mining Concepts and Techniques TUT. September 12, 2013 Data Mining: Concepts and Techniques 1 Data Mining: Concepts and Techniques вЂ” Slides for Textbook вЂ” вЂ” Chapter 6 вЂ” В©Jiawei Han and Micheline Kamber Intelligent Database Systems Research Lab Simon Fraser University, Ari Visa, , Institute of Signal Processing Tampere University of Technology . September 12, 2013 Data Mining: Concepts and Techniques 2 Mining Association, May 18, 2003 Data Mining: Concepts and Techniques 19 Chapter 6: Mining Association Rules in Large Databases! Association rule mining! Multilevel and Multidimensional association rules! From association mining to correlation analysis! Summary May 18, 2003 Data Mining: Concepts and Techniques 20 Multiple-Level Association Rules! Items often form.

4. CHAPTER 1. INTRODUCTION (d) Describe the steps involved in data mining when viewed as a process of knowledge discovery. The steps involved in data mining when viewed as a process of knowledge Data Mining Concepts and Techniques, Third Edition by Jiawei Han, Micheline Kamber, Jian Pei (Solution Manual) ISBN-13: 978-0123814791 ISBN-10: 0123814790 Instant Access After Placing The Order. All The Chapters Are Included.

4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data 4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data

Data Mining: Concepts and Techniques вЂ” Chapter 10. Part 2 вЂ” вЂ” Mining Text and Web Data вЂ” Jiawei Han and Micheline Kamber Department of Computer Science UвЂ¦ Data Mining: Concepts and Techniques . Chapter I: Introduction to Data Mining We are in an age often referred to as the information age. In this information age, because we believe that information leads to power and success, and thanks to sophisticated technologies such as computers, satellites, etc., we have been collecting tremendous amounts of information. Initially, with the advent of

May 18, 2003 Data Mining: Concepts and Techniques 19 Chapter 6: Mining Association Rules in Large Databases! Association rule mining! Multilevel and Multidimensional association rules! From association mining to correlation analysis! Summary May 18, 2003 Data Mining: Concepts and Techniques 20 Multiple-Level Association Rules! Items often form 20/05/2019В В· Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream

May 18, 2003 Data Mining: Concepts and Techniques 19 Chapter 6: Mining Association Rules in Large Databases! Association rule mining! Multilevel and Multidimensional association rules! From association mining to correlation analysis! Summary May 18, 2003 Data Mining: Concepts and Techniques 20 Multiple-Level Association Rules! Items often form 4 Data Mining: Concepts and Techniques 19 Data Mining вЂ“ what kinds of patterns? Classification and prediction Construct models (functions) that describe and distinguish classes or concepts for future prediction. The derived model is based on analyzing training data вЂ“ data whose class labels are known.

Table 4.1: A crosstab for birth place of Programmers and DBAs. - "Data Mining : Concepts and Techniques 2 nd Edition Solution Manual" 4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data

September 10, 2014 Data Mining: Concepts and Techniques 1 Data Mining: Concepts and Techniques вЂ” Slides for Textbook вЂ” вЂ” Chapter 4 вЂ” В©Jiawei Han and Micheline Kamber Intelligent Database Systems Research Lab Simon Fraser University, Ari Visa, , Institute of Signal Processing Tampere University of Technology . Top languages for analytics/data mining programming (KDD Nuggets Poll 4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data

CHAPTER 1. DATA MINING AND ANALYSIS 4 Chapter 1 Data Mining and Analysis Data mining is the process of discovering insightful, interesting, and novel patterns, as well as descriptive, understandable and predictive models from large-scale data. We begin this chapter by looking at basic properties of data modeled as a data ma-trix. We emphasize 20/05/2019В В· Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream

20/05/2019В В· Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream 4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data

4 Data Mining: Concepts and Techniques 19 Data Mining вЂ“ what kinds of patterns? Classification and prediction Construct models (functions) that describe and distinguish classes or concepts for future prediction. The derived model is based on analyzing training data вЂ“ data whose class labels are known. Data Mining: Concepts and Techniques вЂ” Chapter 10. Part 2 вЂ” вЂ” Mining Text and Web Data вЂ” Jiawei Han and Micheline Kamber Department of Computer Science UвЂ¦

Data Mining: Concepts and Techniques . Chapter I: Introduction to Data Mining We are in an age often referred to as the information age. In this information age, because we believe that information leads to power and success, and thanks to sophisticated technologies such as computers, satellites, etc., we have been collecting tremendous amounts of information. Initially, with the advent of 4. CHAPTER 1. INTRODUCTION (d) Describe the steps involved in data mining when viewed as a process of knowledge discovery. The steps involved in data mining when viewed as a process of knowledge

Data Mining Concepts and Techniques TUT. Table 4.1: A crosstab for birth place of Programmers and DBAs. - "Data Mining : Concepts and Techniques 2 nd Edition Solution Manual", CHAPTER 1. DATA MINING AND ANALYSIS 4 Chapter 1 Data Mining and Analysis Data mining is the process of discovering insightful, interesting, and novel patterns, as well as descriptive, understandable and predictive models from large-scale data. We begin this chapter by looking at basic properties of data modeled as a data ma-trix. We emphasize.

### Data Mining Concepts and Techniques ? Chapter 10. Part 2

Data Mining Concepts and Techniques TUT. CHAPTER 1. DATA MINING AND ANALYSIS 4 Chapter 1 Data Mining and Analysis Data mining is the process of discovering insightful, interesting, and novel patterns, as well as descriptive, understandable and predictive models from large-scale data. We begin this chapter by looking at basic properties of data modeled as a data ma-trix. We emphasize, CHAPTER 1. DATA MINING AND ANALYSIS 4 Chapter 1 Data Mining and Analysis Data mining is the process of discovering insightful, interesting, and novel patterns, as well as descriptive, understandable and predictive models from large-scale data. We begin this chapter by looking at basic properties of data modeled as a data ma-trix. We emphasize.

### Data Mining Concepts and Techniques ? Chapter 10. Part 2

Data Mining Concepts and Techniques TUT. Data Mining: Concepts and Techniques . Chapter I: Introduction to Data Mining We are in an age often referred to as the information age. In this information age, because we believe that information leads to power and success, and thanks to sophisticated technologies such as computers, satellites, etc., we have been collecting tremendous amounts of information. Initially, with the advent of https://en.wikipedia.org/wiki/Bioinformatics Data Mining: Concepts and Techniques вЂ” Chapter 10. Part 2 вЂ” вЂ” Mining Text and Web Data вЂ” Jiawei Han and Micheline Kamber Department of Computer Science UвЂ¦.

Data Mining Concepts and Techniques, Third Edition by Jiawei Han, Micheline Kamber, Jian Pei (Solution Manual) ISBN-13: 978-0123814791 ISBN-10: 0123814790 Instant Access After Placing The Order. All The Chapters Are Included. 4 Data Mining: Concepts and Techniques 19 Data Mining вЂ“ what kinds of patterns? Classification and prediction Construct models (functions) that describe and distinguish classes or concepts for future prediction. The derived model is based on analyzing training data вЂ“ data whose class labels are known.

CHAPTER 1. DATA MINING AND ANALYSIS 4 Chapter 1 Data Mining and Analysis Data mining is the process of discovering insightful, interesting, and novel patterns, as well as descriptive, understandable and predictive models from large-scale data. We begin this chapter by looking at basic properties of data modeled as a data ma-trix. We emphasize 20/05/2019В В· Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream

Data Mining: Concepts and Techniques . Chapter I: Introduction to Data Mining We are in an age often referred to as the information age. In this information age, because we believe that information leads to power and success, and thanks to sophisticated technologies such as computers, satellites, etc., we have been collecting tremendous amounts of information. Initially, with the advent of September 12, 2013 Data Mining: Concepts and Techniques 1 Data Mining: Concepts and Techniques вЂ” Slides for Textbook вЂ” вЂ” Chapter 6 вЂ” В©Jiawei Han and Micheline Kamber Intelligent Database Systems Research Lab Simon Fraser University, Ari Visa, , Institute of Signal Processing Tampere University of Technology . September 12, 2013 Data Mining: Concepts and Techniques 2 Mining Association

Table 4.1: A crosstab for birth place of Programmers and DBAs. - "Data Mining : Concepts and Techniques 2 nd Edition Solution Manual" Data Mining: Concepts and Techniques. Article В· January 2006 with 732 Reads How we measure 'reads' A 'read' is counted each time someone views a publication summary (such as the title, abstract

Data Mining: Concepts and Techniques . Chapter I: Introduction to Data Mining We are in an age often referred to as the information age. In this information age, because we believe that information leads to power and success, and thanks to sophisticated technologies such as computers, satellites, etc., we have been collecting tremendous amounts of information. Initially, with the advent of 4. CHAPTER 1. INTRODUCTION (d) Describe the steps involved in data mining when viewed as a process of knowledge discovery. The steps involved in data mining when viewed as a process of knowledge

Data Mining: Concepts and Techniques. Article В· January 2006 with 732 Reads How we measure 'reads' A 'read' is counted each time someone views a publication summary (such as the title, abstract Data Mining Concepts and Techniques, Third Edition by Jiawei Han, Micheline Kamber, Jian Pei (Solution Manual) ISBN-13: 978-0123814791 ISBN-10: 0123814790 Instant Access After Placing The Order. All The Chapters Are Included.

20/05/2019В В· Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream Data Mining: Concepts and Techniques вЂ” Chapter 10. Part 2 вЂ” вЂ” Mining Text and Web Data вЂ” Jiawei Han and Micheline Kamber Department of Computer Science UвЂ¦

## Data Mining Concepts and Techniques TUT

Data Mining Concepts and Techniques ? Chapter 10. Part 2. 20/05/2019В В· Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream, Data Mining: Concepts and Techniques. Article В· January 2006 with 732 Reads How we measure 'reads' A 'read' is counted each time someone views a publication summary (such as the title, abstract.

### Data Mining Concepts and Techniques ? Chapter 10. Part 2

Data Mining Concepts and Techniques ? Chapter 10. Part 2. Data Mining: Concepts and Techniques. Article В· January 2006 with 732 Reads How we measure 'reads' A 'read' is counted each time someone views a publication summary (such as the title, abstract, 20/05/2019В В· Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream.

May 18, 2003 Data Mining: Concepts and Techniques 19 Chapter 6: Mining Association Rules in Large Databases! Association rule mining! Multilevel and Multidimensional association rules! From association mining to correlation analysis! Summary May 18, 2003 Data Mining: Concepts and Techniques 20 Multiple-Level Association Rules! Items often form 4. CHAPTER 1. INTRODUCTION (d) Describe the steps involved in data mining when viewed as a process of knowledge discovery. The steps involved in data mining when viewed as a process of knowledge

Data Mining: Concepts and Techniques . Chapter I: Introduction to Data Mining We are in an age often referred to as the information age. In this information age, because we believe that information leads to power and success, and thanks to sophisticated technologies such as computers, satellites, etc., we have been collecting tremendous amounts of information. Initially, with the advent of Table 4.1: A crosstab for birth place of Programmers and DBAs. - "Data Mining : Concepts and Techniques 2 nd Edition Solution Manual"

September 12, 2013 Data Mining: Concepts and Techniques 1 Data Mining: Concepts and Techniques вЂ” Slides for Textbook вЂ” вЂ” Chapter 6 вЂ” В©Jiawei Han and Micheline Kamber Intelligent Database Systems Research Lab Simon Fraser University, Ari Visa, , Institute of Signal Processing Tampere University of Technology . September 12, 2013 Data Mining: Concepts and Techniques 2 Mining Association 20/05/2019В В· Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream

4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data Table 4.1: A crosstab for birth place of Programmers and DBAs. - "Data Mining : Concepts and Techniques 2 nd Edition Solution Manual"

20/05/2019В В· Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream Data Mining Concepts and Techniques, Third Edition by Jiawei Han, Micheline Kamber, Jian Pei (Solution Manual) ISBN-13: 978-0123814791 ISBN-10: 0123814790 Instant Access After Placing The Order. All The Chapters Are Included.

September 12, 2013 Data Mining: Concepts and Techniques 1 Data Mining: Concepts and Techniques вЂ” Slides for Textbook вЂ” вЂ” Chapter 6 вЂ” В©Jiawei Han and Micheline Kamber Intelligent Database Systems Research Lab Simon Fraser University, Ari Visa, , Institute of Signal Processing Tampere University of Technology . September 12, 2013 Data Mining: Concepts and Techniques 2 Mining Association September 10, 2014 Data Mining: Concepts and Techniques 1 Data Mining: Concepts and Techniques вЂ” Slides for Textbook вЂ” вЂ” Chapter 4 вЂ” В©Jiawei Han and Micheline Kamber Intelligent Database Systems Research Lab Simon Fraser University, Ari Visa, , Institute of Signal Processing Tampere University of Technology . Top languages for analytics/data mining programming (KDD Nuggets Poll

4. CHAPTER 1. INTRODUCTION (d) Describe the steps involved in data mining when viewed as a process of knowledge discovery. The steps involved in data mining when viewed as a process of knowledge 4 Data Mining: Concepts and Techniques 19 Data Mining вЂ“ what kinds of patterns? Classification and prediction Construct models (functions) that describe and distinguish classes or concepts for future prediction. The derived model is based on analyzing training data вЂ“ data whose class labels are known.

4 Data Mining: Concepts and Techniques 19 Data Mining вЂ“ what kinds of patterns? Classification and prediction Construct models (functions) that describe and distinguish classes or concepts for future prediction. The derived model is based on analyzing training data вЂ“ data whose class labels are known. CHAPTER 1. DATA MINING AND ANALYSIS 4 Chapter 1 Data Mining and Analysis Data mining is the process of discovering insightful, interesting, and novel patterns, as well as descriptive, understandable and predictive models from large-scale data. We begin this chapter by looking at basic properties of data modeled as a data ma-trix. We emphasize

4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data Data Mining: Concepts and Techniques вЂ” Chapter 10. Part 2 вЂ” вЂ” Mining Text and Web Data вЂ” Jiawei Han and Micheline Kamber Department of Computer Science UвЂ¦

4 Data Mining: Concepts and Techniques 19 Data Mining вЂ“ what kinds of patterns? Classification and prediction Construct models (functions) that describe and distinguish classes or concepts for future prediction. The derived model is based on analyzing training data вЂ“ data whose class labels are known. Data Mining: Concepts and Techniques вЂ” Chapter 10. Part 2 вЂ” вЂ” Mining Text and Web Data вЂ” Jiawei Han and Micheline Kamber Department of Computer Science UвЂ¦

4 Data Mining: Concepts and Techniques 19 Data Mining вЂ“ what kinds of patterns? Classification and prediction Construct models (functions) that describe and distinguish classes or concepts for future prediction. The derived model is based on analyzing training data вЂ“ data whose class labels are known. 20/05/2019В В· Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream

May 18, 2003 Data Mining: Concepts and Techniques 19 Chapter 6: Mining Association Rules in Large Databases! Association rule mining! Multilevel and Multidimensional association rules! From association mining to correlation analysis! Summary May 18, 2003 Data Mining: Concepts and Techniques 20 Multiple-Level Association Rules! Items often form 4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data

Data Mining Concepts and Techniques TUT. Data Mining Concepts and Techniques, Third Edition by Jiawei Han, Micheline Kamber, Jian Pei (Solution Manual) ISBN-13: 978-0123814791 ISBN-10: 0123814790 Instant Access After Placing The Order. All The Chapters Are Included., 4 Data Mining: Concepts and Techniques 19 Data Mining вЂ“ what kinds of patterns? Classification and prediction Construct models (functions) that describe and distinguish classes or concepts for future prediction. The derived model is based on analyzing training data вЂ“ data whose class labels are known..

### Data Mining Concepts and Techniques TUT

Data Mining Concepts and Techniques TUT. 4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data, 4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data.

### Data Mining Concepts and Techniques TUT

Data Mining Concepts and Techniques ? Chapter 10. Part 2. CHAPTER 1. DATA MINING AND ANALYSIS 4 Chapter 1 Data Mining and Analysis Data mining is the process of discovering insightful, interesting, and novel patterns, as well as descriptive, understandable and predictive models from large-scale data. We begin this chapter by looking at basic properties of data modeled as a data ma-trix. We emphasize https://en.wikipedia.org/wiki/Bioinformatics 4. CHAPTER 1. INTRODUCTION (d) Describe the steps involved in data mining when viewed as a process of knowledge discovery. The steps involved in data mining when viewed as a process of knowledge.

May 18, 2003 Data Mining: Concepts and Techniques 19 Chapter 6: Mining Association Rules in Large Databases! Association rule mining! Multilevel and Multidimensional association rules! From association mining to correlation analysis! Summary May 18, 2003 Data Mining: Concepts and Techniques 20 Multiple-Level Association Rules! Items often form 20/05/2019В В· Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream

Data Mining: Concepts and Techniques. Article В· January 2006 with 732 Reads How we measure 'reads' A 'read' is counted each time someone views a publication summary (such as the title, abstract September 12, 2013 Data Mining: Concepts and Techniques 1 Data Mining: Concepts and Techniques вЂ” Slides for Textbook вЂ” вЂ” Chapter 6 вЂ” В©Jiawei Han and Micheline Kamber Intelligent Database Systems Research Lab Simon Fraser University, Ari Visa, , Institute of Signal Processing Tampere University of Technology . September 12, 2013 Data Mining: Concepts and Techniques 2 Mining Association

September 12, 2013 Data Mining: Concepts and Techniques 1 Data Mining: Concepts and Techniques вЂ” Slides for Textbook вЂ” вЂ” Chapter 6 вЂ” В©Jiawei Han and Micheline Kamber Intelligent Database Systems Research Lab Simon Fraser University, Ari Visa, , Institute of Signal Processing Tampere University of Technology . September 12, 2013 Data Mining: Concepts and Techniques 2 Mining Association 4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data

20/05/2019В В· Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream Data Mining: Concepts and Techniques . Chapter I: Introduction to Data Mining We are in an age often referred to as the information age. In this information age, because we believe that information leads to power and success, and thanks to sophisticated technologies such as computers, satellites, etc., we have been collecting tremendous amounts of information. Initially, with the advent of

Table 4.1: A crosstab for birth place of Programmers and DBAs. - "Data Mining : Concepts and Techniques 2 nd Edition Solution Manual" 4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data

CHAPTER 1. DATA MINING AND ANALYSIS 4 Chapter 1 Data Mining and Analysis Data mining is the process of discovering insightful, interesting, and novel patterns, as well as descriptive, understandable and predictive models from large-scale data. We begin this chapter by looking at basic properties of data modeled as a data ma-trix. We emphasize Data Mining: Concepts and Techniques . Chapter I: Introduction to Data Mining We are in an age often referred to as the information age. In this information age, because we believe that information leads to power and success, and thanks to sophisticated technologies such as computers, satellites, etc., we have been collecting tremendous amounts of information. Initially, with the advent of

4/7/2003 Data Mining: Concepts and Techniques 26 Chapter 3: Data Preprocessing! Why preprocess the data?! Data cleaning ! Data integration and transformation! Data reduction! Discretization and concept hierarchy generation! Summary 4/7/2003 Data Mining: Concepts and Techniques 27 Data Reduction Strategies! Warehouse may store terabytes of data 4 Data Mining: Concepts and Techniques 19 Data Mining вЂ“ what kinds of patterns? Classification and prediction Construct models (functions) that describe and distinguish classes or concepts for future prediction. The derived model is based on analyzing training data вЂ“ data whose class labels are known.