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CSc 4740/6740 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 Chapter 6 Mining Frequent Patterns, Association and Correlations: Basic Concepts and Methods |Lecture for Chapter 8 Classification: Basic Concepts |Lecture for Chapter 9 Classification: Advanced Methods

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Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data.

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Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data.

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Data Mining: Concepts and Techniques — Slides for Textbook — — Chapter 5 — 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.

### Data Mining: Concepts and Techniques

17 Data Mining: Concepts and Techniques February 10, 2014 (a i +a i+1 )/2 is the midpoint between the values of a i and a i+1 The point with the minimum expected information requirement for A is

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knowledge mining which emphasis on mining from large amounts of data. It is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems.

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Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data.

### Data Mining: Concepts and Techniques

20 Data Mining: Concepts and Techniques Data mining: Discovering interesting patterns from large amounts of data A natural evolution of database technology, in great demand, with wide applications A KDD process includes data cleaning, data integration, data selection, transformation, data mining, pattern evaluation, and knowledge presentation

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October 8, 2015 Data Mining: Concepts and Techniques 20 Gini index (CART, IBM IntelligentMiner) If a data set D contains examples from nclasses, gini index, gini(D) is defined as where p j is the relative frequency of class jin D If a data set D is split on A into two subsets D 1 and D 2, the giniindex gini(D) is defined as Reduction in Impurity:

### CS 412: Introduction to Data Mining Course Syllabus

CS 412: Introduction to Data Mining Course Syllabus Course Description This course is an introductory course on data mining. It introduces the basic concepts, principles, methods, implementation techniques, and applications of data mining, with a focus on two major data mining functions: (1) pattern discovery and (2) cluster analysis.

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### Data Mining: Concepts and Techniques - Sabancı Üniversitesi

Data Mining: Concepts and Techniques - Sabancı Üniversitesi

### Data Mining: Overview - MIT OpenCourseWare

Data Mining: Overview What is Data Mining? • Recently* coined term for confluence of ideas from statistics and computer science (machine learning and database methods) applied to large databases in science, engineering and business. • In a state of flux, many definitions, lot of debate about what it is and what it is not. Terminology not

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اسلاید 31: January 3, 2018Data Mining: Concepts and Techniques31Major Issues in Data Mining (1)Mining methodology and user interactionMining different kinds of knowledge in databasesInteractive mining of knowledge at multiple levels of abstractionIncorporation of background knowledgeData mining query languages and ad-hoc data ...

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April 14, 201 8 Data Mining: Concept s and Techniques 3 Mining Complex Data Objects: Generalization of Structured Data Set-valued attribute Generalization of each value in the set into its corresponding higher-level concepts Derivation of the general behavior of the set, such as the number of elements in the set, the types or value ranges in ...

### Data Mining: Concepts and Techniques

Some of the exercises in Data Mining: Concepts and Techniques are themselves good research topics that may lead to future Master or Ph.D. theses. Therefore, our solution manual is intended to be used as a guide in answering the exercises of the textbook. You are welcome to

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July 13, 2014 Data Mining: Concepts and Techniques 4 Sequence Databases & Sequential Patterns Transaction databases, time-series databases vs. sequence databases Frequent patterns vs. (frequent) sequential patterns Applications of sequential pattern mining Customer shopping sequences: First buy computer, then CD-ROM, and then digital camera, within 3 months.

### Data mining - Wikipedia

Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the information into a comprehensible structure for ...

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These methods may also help detect outliers. Classification according to the kinds of techniques utilized: Data mining systems can be categorized according to the underlying data mining techniques …

### Data Mining | Coursera

The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization.

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April 3, 2003 Data Mining: Concepts and Techniques 12 Major Issues in Data Mining (2) Issues relating to the diversity of data types! Handling relational and complex types of data! Mining information from heterogeneous databases and global information systems (WWW)! Issues related to applications and social impacts! Application of discovered ...

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### Data Mining In Excel: Lecture Notes and Cases

XLMiner is a comprehensive data mining add-in for Excel, which is easy to learn for users of Excel. It is a tool to help you get quickly started on data mining, oﬁering a variety of methods to analyze data. It has extensive coverage of statistical and data mining techniques for classiﬂcation, prediction, a–nity analysis, and data ...