Analyzing and modeling complex and big data professor maria fasli tedxuniversityofessex duration. Classification and prediction construct models functions that describe and distinguish classes or concepts. Concepts and techniques chapter 3 a free powerpoint ppt presentation displayed as a flash slide show on id. Updated slides for cs, uiuc teaching in powerpoint form. The introductory chapter uses the decision tree classifier for illustration, but the discussion on many. Chapter 1 pro vides an in tro duction to the m ultidisciplinary eld of data mining. Applications and trends in data mining get slides in pdf.
The course uses many examples using reallife event logs to illustrate the concepts and algorithms. Lecture notes data mining sloan school of management. Statisticians were the first to use the term data mining. Concepts and techniques slides for textbook chapter 1 jiawei han and micheline kamber intelligent database systems research lab school of computing science simon fraser. Concepts and techniques chapter 1 introduction jiawei han and december 26, 20. Concepts and techniques are themselves good research topics that may lead to future master or ph. Basic concepts, decision trees, and model evaluation lecture notes for chapter 4 introduction to data mining by tan, steinbach, kumar.
Data mining techniques should be able to handle noise in data or incomplete information. Learn vocabulary, terms, and more with flashcards, games, and other study tools. It discusses the ev olutionary path of database tec hnology whic h led up to the need for data mining, and the. Mining association rules in large databases chapter 7. Concepts and techniques slides for textbook chapter 1. Basic concepts and techniques lecture notes for chapter 3 introduction to data mining, 2nd edition by tan, steinbach, karpatne, kumar 02032020. Concepts and techniques slides for textbook chapter 1 jiawei han and micheline kamberintelligent database systems research lab simon fraser university, ari visa, institute of signal processing tampere university of technology october 3, 2010 data mining. Concepts and techniques chapter 1 introduction jiawei han and micheline kamber department of computer science university of illinois at urbanachampaign. Concepts and techniques 4 classification predicts categorical class labels discrete or nominal classifies data constructs a model based on the training set. Provides both theoretical and practical coverage of all data mining topics. Lingma acheson department of computer and information science, iupui. Introduction to data mining and architecture in hindi. A multi dimensional view of data mining what kinds of data can be mined. Knowledge presentation mined knowledge is presented to the user with visualization or representation techniques.
After taking this course, one is able to run process mining projects. Concepts and techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Ppt chapter 1 introduction to data mining powerpoint. Concepts and techniques, 3rd edition jiawei han, micheline kamber, jian pei database modeling and design. The theory will be complemented by handson applied studies on problems in financial engineering, ecommerce, geosciences, bioinformatics and elsewhere. The process of finding a model that describes and distinguishes the data classes or concepts, for.
Comprehend the concepts of data preparation, data cleansing and exploratory data analysis. Data mining primitives, languages, and system architectures. The morgan kaufmann series in data management systems. Data warehouse and olap technology for data mining.
Concepts and techniques chapter 1 introduction jiawei han and micheline kamber department of computer science. Practical machine learning tools and techniques, fourth edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools. Confluence of multiple disciplines data mining database technology statistics other disciplines information science machine learning visualization april 3, 2003 data mining. Chapter 1 data mining in this intoductory chapter we begin with the essence of data mining and a discussion of how data mining is treated by the various disciplines that contribute to this. One of the important subfield in data mining is itemset mining, which consists of discovering appealing and useful patterns. Data warehousing and data mining table of contents objectives context. More than the size of data, the size of the search space is even more decisive for data mining.
Jiawei han and micheline kamber department of computer science. Concepts and techniques 19 data mining what kinds of patterns. Perform text mining to enable customer sentiment analysis. Chapter 1 introduction to data mining outline motivation of data mining concepts of data mining applications of data mining data mining functionalities focus of data. Association rules market basket analysis pdf han, jiawei, and micheline kamber. Csc 47406740 data mining tentative lecture notes lecture for chapter 1 introduction lecture for chapter 2 getting to know your data lecture for chapter 3 data preprocessing lecture for.