Data Mining: Concepts and Techniques Slides for Textbook Chapter 8

Nov 30, 2012

1k likes | 1.2k Views

November 29, 2012. Data Mining: Concepts and Techniques. 2. Chapter 8. Cluster Analysis. What is Cluster Analysis?Types of Data in Cluster AnalysisA Categorization of Major Clustering MethodsPartitioning MethodsHierarchical MethodsDensity-Based MethodsGrid-Based MethodsModel-Based Clustering

Share Presentation

Embed Code

Link

therese

Download Presentation

Data Mining: Concepts and Techniques Slides for Textbook Chapter 8

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

Data Mining Techniques for CRM

Data Mining Techniques for CRM. Seyyed Jamaleddin Pishvayi Customer Relationship Management Instructor : Dr. Taghiyare Tehran University Spring 1383. Outlines. What is Data Mining? Data Mining Motivation Data Mining Applications Applications of Data Mining in CRM Data Mining Taxonomy

740 views • 35 slides

Data Mining: Concepts and Techniques

Some of these slides are taken with some modifications from:. Data Mining: Concepts and Techniques. © Jiawei Han and Micheline Kamber Intelligent Database Systems Research Lab School of Computing Science Simon Fraser University, Canada http://www.cs.sfu.ca. Acknowledgements.

1.41k views • 68 slides

Chapter 7: Text mining

Chapter 7: Text mining. Text mining. It refers to data mining using text documents as data. There are many special techniques for pre-processing text documents to make them suitable for mining. Most of these techniques are from the field of “Information Retrieval”. .

1.22k views • 49 slides

Chapter 2 Data Mining

Chapter 2 Data Mining. Faculty of Computer Science and Engineering HCM City University of Technology October- 2010. Outline. Overview of data mining Association rules Classification Regression Clustering Other Data Mining problems Applications of data mining. DATA MINING.

2.27k views • 154 slides

CS/CMPE 536 –Data Mining

CS/CMPE 536 –Data Mining. Outline . Description. A comprehensive introduction to the concepts and techniques in data mining data mining process – its need and motivation data mining tasks and functionalities association rule mining clustering text and web mining mining sequential data

340 views • 15 slides

Data Mining

Data Mining. Introduction BIM. Objectives. Nature of Data Mining Data Mining Tools Ethics Online Survey Techniques Interpret Data. Overview. Data Mining (data or knowledge discovery)

478 views • 15 slides

Data Mining: Concepts and Techniques

Data Mining: Concepts and Techniques . Chapter 1. Introduction. Motivation: Why data mining? What is data mining? Data Mining: On what kind of data? Data mining functionality Are all the patterns interesting? Major issues in data mining.

871 views • 37 slides

Data Mining Practical Machine Learning Tools and Techniques

Data Mining Practical Machine Learning Tools and Techniques Slides for Chapter 2 of Data Mining by I. H. Witten, E. Frank and M. A. Hall. Input: Concepts, instances, attributes. Terminology What’s a concept? Classification, association, clustering, numeric prediction

607 views • 35 slides

Data Mining Techniques for CRM

Data Mining Techniques for CRM. Lakewood Resource And Referral Center 212 2 nd Street Lakewood NJ, 08701. Outlines. What is Data Mining? Data Mining Motivation Data Mining Applications Applications of Data Mining in CRM Data Mining Taxonomy Data Mining Techniques. Data Mining.

501 views • 30 slides

Data Mining: Concepts and Techniques — Chapter 2 —

Data Mining: Concepts and Techniques — Chapter 2 —. Chapter 2: Data Preprocessing. Why preprocess the data? Descriptive data summarization Data cleaning Data integration and transformation Data reduction Discretization and concept hierarchy generation Summary. Why Data Preprocessing?.

943 views • 68 slides

Data Mining: Concepts and Techniques — Additional Applications and Emerging Topics —

Data Mining: Concepts and Techniques — Additional Applications and Emerging Topics —. Li Xiong Slides credits: Jiawei Han and Micheline Kamber Chris Clifton Agrawal and Srikant. Outline. Biological data mining Data mining for intrusion detection Privacy-preserving data mining.

673 views • 45 slides

Data Mining: Concepts and Techniques — Chapter 8 — 8.2 Mining time-series data

Data Mining: Concepts and Techniques — Chapter 8 — 8.2 Mining time-series data. Chapter 8. Mining Stream, Time-Series, and Sequence Data. Mining data streams Mining time-series data Mining sequence patterns in transactional databases Mining sequence patterns in biological data.

567 views • 25 slides

Data Mining: Concepts and Techniques

Data Mining: Concepts and Techniques. By N.Gopinath AP/CSE. Chapter 1. Introduction. Motivation: Why data mining? What is data mining? Data Mining: On what kind of data? Data mining functionality Are all the patterns interesting? Classification of data mining systems

1.05k views • 48 slides

Data Mining: Concepts and Techniques — Chapter 3 —

Data Mining: Concepts and Techniques — Chapter 3 —. Jiawei Han and Micheline Kamber. Chapter 3: Data Warehousing and OLAP Technology: An Overview. What is a data warehouse? A multi-dimensional data model Data warehouse architecture Data warehouse implementation

1.15k views • 47 slides

Data Mining: Concepts and Techniques

Data Mining: Concepts and Techniques. Programme of Computer Science and Technology United International College. Chapter 3: Data Warehousing, and On-line Analytical Processing. Data warehouse: Basic concept Data warehouse modeling: Data cube and OLAP Data warehouse architecture

740 views • 54 slides

Data Mining: Concepts and Techniques — Chapter 9 — Graph mining and Social Network Analysis

Data Mining: Concepts and Techniques — Chapter 9 — Graph mining and Social Network Analysis. Li Xiong Slides credits: Jiawei Han and Micheline Kamber. Graph Mining and Social Network Analysis. Graph mining Frequent subgraph mining Social network analysis Social network

2.13k views • 62 slides

Data Mining: Concepts and Techniques — Chapter 1 — — Introduction —

Data Mining: Concepts and Techniques — Chapter 1 — — Introduction —. Slides Adapted from Book Authors. About the course. We cover some major problems in Data Mining. The focus is on Database and algorithmic aspects Main reference:

780 views • 51 slides

Session – I Data Mining : Concepts and Techniques

Session – I Data Mining : Concepts and Techniques. Dr. JULIE M. DAVID Asst. Professor Department of Computer Applications MES College, Marampally, Aluva. Why Data Mining?. The Explosive Growth of Data: from terabytes to petabytes Data collection and data availability

785 views • 60 slides

Chapter One

Chapter One. Introduction. Chapter Overview. Roles of data, information and knowledge Background of data mining What is data mining? Main data mining objectives Data mining and other related disciplines Current state of data mining Promises and challenges

556 views • 24 slides

Data Mining: Concepts and Techniques (3 rd ed.) — Chapter 10 —

Data Mining: Concepts and Techniques (3 rd ed.) — Chapter 10 —. Chapter 10. Cluster Analysis: Basic Concepts and Methods. Cluster Analysis: Basic Concepts Partitioning Methods Hierarchical Methods Density-Based Methods Grid-Based Methods Evaluation of Clustering Summary. 2. 2.

1.83k views • 136 slides

Data Mining: Concepts and Techniques — Chapter 2 —

Data Mining: Concepts and Techniques — Chapter 2 —. What is about Data?. General data characteristics Basic data description and exploration Measuring data similarity. What is Data?. Attributes. Collection of data objects and their attributes

738 views • 62 slides

CS 536 –Data Mining

CS 536 –Data Mining. Outline. Description. A comprehensive introduction to the concepts and techniques in data mining data mining process – its need and motivation data mining tasks and functionalities role of data warehousing association rule mining classification and prediction

565 views • 15 slides

More Related