data mining concepts and techniques han and kamber 2nd edition free download
Data Mining Concepts and Techniques phần 1 potx
... Reference Data in Enterprise Databases: Binding Corporate Data to the Wider WorldMalcolm Chisholm Data Mining: Concepts and Techniques Jiawei Han and Micheline Kamber Understanding SQL and Java ... Statistical Data Mining 66611.3.3 Visual and Audio Data Mining 66711.3.4 Data Mining and Collaborative Filtering 67011.4 Social Impacts of Data Mining 67511.4.1 Ubiquitous and Invisible Data Mining ... object-relational databases and specific application-oriented databases, such as spatial databases, time-series databases,text databases, and multimedia databases. The challenges and techniques of mining...
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Data Mining Concepts and Techniques phần 2 ppsx
... the original data. PCA is computationally inexpensive, can be applied to ordered and unorderedattributes, and can handle sparse data and skewed data. Multidimensional data of more than two dimensions ... (inclusive).2.3 Data Cleaning 652.3.3 Data Cleaning as a ProcessMissing values, noise, and inconsistencies contribute to inaccurate data. So far, we havelooked at techniques for handling missing data and ... 972.7Summary Data preprocessing is an important issue for both data warehousing and data mining, as real-world data tend to be incomplete, noisy, and inconsistent. Data preprocessingincludes data cleaning,...
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Data Mining Concepts and Techniques phần 3 docx
... processing, and data mining. We also introduce on-line analytical mining (OLAM), a powerful paradigm thatintegrates OLAP with data mining technology.3.5.1 Data Warehouse Usage Data warehouses and data ... summarized data in a data warehouse sets a solid foundation for successful data mining. Moreover, we also believe that data mining should be a human-centered process.Rather than asking a data mining ... Warehouse and OLAP Technology: An Overview3.5From Data Warehousing to Data Mining “How do data warehousing and OLAP relate to data mining? ” In this section, we study theusage of data warehousing...
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Oracle9i Data Mining Concepts Release 9.2.0.2 October 2002 Part No. A95961-02 Oracle9i Data
... faster than the viii Basic ODM Concepts 1-11Basic ODM Concepts Oracle9i Data Mining (ODM) embeds data mining within the Oracle9i database. The data never leaves the database — the data, data ... SQL/MM for Data Mining. JDM has also influenced these standards. Oracle9i Data Mining will comply with the JDM standard when that standard is published.1.2.2 Data Mining ServerThe Data Mining ... main components:■Oracle9i Data Mining API ■ Data Mining Server (DMS)1.2.1 Oracle9i Data Mining APIThe Oracle9i Data Mining API is the component of Oracle9i Data Mining that allows users to...
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Data Mining Classification: Alternative Techniques - Lecture Notes for Chapter 5 Introduction to Data Mining pdf
... by R1© Tan,Steinbach, Kumar Introduction to Data Mining 36 Instance Based ClassifiersExamples:–Rote-learner• Memorizes entire training data and performs classification only if attributes ... $10K to $1M© Tan,Steinbach, Kumar Introduction to Data Mining 40 1 nearest-neighborVoronoi Diagram© Tan,Steinbach, Kumar Introduction to Data Mining 38 Nearest-Neighbor ClassifiersRequires ... r* and r’ • Choose rule set that minimizes MDL principle–Repeat rule generation and rule optimization for the remaining positive examples© Tan,Steinbach, Kumar Introduction to Data Mining...
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cosmology the origin and evolution of cosmic structure, 2nd edition the origin and evolution of cosmic structure
... from the metric gij and its first and second derivatives, and islinear in the second derivative. This modification does not change the covariantcharacter of the equations, and does not alter the ... thank SabinoMatarrese, Lauro Moscardini and Bepi Tormen for their careful reading of themanuscript and for many discussions on other matters related to the book. Wealso thank Varun Sahni and ... appar-ent luminosity greater than some limit l and redshift less than z. These relationsare also important because, in principle, they provide a way of determining thedeceleration parameter...
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Data Mining Classification: Basic Concepts, Decision Trees, and Model Evaluation Lecture Notes for Chapter 4 Introduction to Data Mining pptx
... Married 80K ? 10 Test Data © Tan,Steinbach, Kumar Introduction to Data Mining 25 Splitting Based on Continuous Attributes© Tan,Steinbach, Kumar Introduction to Data Mining 46 Tree InductionGreedy ... Tan,Steinbach, Kumar Introduction to Data Mining 3 Illustrating Classification Task© Tan,Steinbach, Kumar Introduction to Data Mining 13 Apply Model to Test Data RefundMarStTaxIncYESNONONOYes ... AttributesTraining Data Model: Decision Tree© Tan,Steinbach, Kumar Introduction to Data Mining 8 Decision Tree Classification TaskDecision Tree© Tan,Steinbach, Kumar Introduction to Data Mining 35...
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Data Mining Association Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 6 Introduction to Data Mining pdf
... Specific-to-general Data Mining Association Analysis: Basic Concepts and AlgorithmsLecture Notes for Chapter 6Introduction to Data Mining byTan, Steinbach, Kumar© Tan,Steinbach, Kumar Introduction to Data ... to Data Mining 49 Effect of Support DistributionMany real data sets have skewed support distributionSupport distribution of a retail data set© Tan,Steinbach, Kumar Introduction to Data Mining ... may decouple the support and confidence requirements© Tan,Steinbach, Kumar Introduction to Data Mining 16 Reducing Number of ComparisonsCandidate counting:–Scan the database of transactions...
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Data Mining Association Rules: Advanced Concepts and Algorithms Lecture Notes for Chapter 7 Introduction to Data Mining docx
... Kumar Introduction to Data Mining 4 Handling Categorical AttributesPotential Issues–What if attribute has many possible values• Example: attribute country has more than 200 possible values• ... pass over the sequence database D to find the support for these candidate sequences–Candidate Elimination:•Eliminate candidate k-sequences whose actual support is less than minsup© Tan,Steinbach, ... > µ + ∆• Z has zero mean and variance 1 under null hypothesis222121'nsnsZ+∆−−=µµ© Tan,Steinbach, Kumar Introduction to Data Mining 3 Handling Categorical AttributesTransform...
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Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining pot
... clusters are irregular or intertwined, and when noise and outliers are present. 6 density-based clusters© Tan,Steinbach, Kumar Introduction to Data Mining 34 Handling Empty ClustersBasic K-means ... Tan,Steinbach, Kumar Introduction to Data Mining 42 Limitations of K-means: Non-globular ShapesOriginal PointsK-means (2 Clusters)© Tan,Steinbach, Kumar Introduction to Data Mining 13 Types of Clusters: ... Kumar Introduction to Data Mining 5 Notion of a Cluster can be AmbiguousHow many clusters?Four Clusters Two Clusters Six Clusters © Tan,Steinbach, Kumar Introduction to Data Mining 41 Limitations...
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Data Mining Cluster Analysis: Advanced Concepts and Algorithms Lecture Notes for Chapter 9 Introduction to Data Mining pot
... to Data Mining 11 Sparsification in the Clustering Process© Tan,Steinbach, Kumar Introduction to Data Mining 22 Experimental Results: CHAMELEON© Tan,Steinbach, Kumar Introduction to Data Mining ... © Tan,Steinbach, Kumar Introduction to Data Mining 35 SNN Clustering Can Handle Other Difficult Situations© Tan,Steinbach, Kumar Introduction to Data Mining 24 Experimental Results: CURE (15 ... Kumar Introduction to Data Mining 18 Experimental Results: CHAMELEON© Tan,Steinbach, Kumar Introduction to Data Mining 16 Chameleon: StepsPreprocessing Step: Represent the Data by a Graph–Given...
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Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management - Second Edition
... of techniques to apply in a particular situation depends on the nature of the data mining task, the nature of the available data, and the skills and preferences of the data miner. Data mining ... By data mining, of course! How Data Mining Was Applied Most data mining methods learn by example. The neural network or decision tree generator or what have you is fed thousands and thousands ... that, on a technical level, the data mining effort is working and the data is reasonably accurate. This can be quite comforting. If the data and the data mining techniques applied to it are powerful...
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