... Reference Data in Enterprise Databases: Binding Corporate Data to the Wider World Malcolm Chisholm Data Mining: Concepts and Techniques Jiawei Han and Micheline Kamber Understanding SQL and Java ... Statistical Data Mining 666 11.3.3 Visual and Audio Data Mining 667 11.3.4 Data Mining and Collaborative Filtering 670 11.4 Social Impacts of Data Mining 675 11.4.1 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...
Ngày tải lên: 08/08/2014, 18:22
... the original data. PCA is computationally inexpensive, can be applied to ordered and unordered attributes, and can handle sparse data and skewed data. Multidimensional data of more than two dimensions ... (inclusive). 2.3 Data Cleaning 65 2.3.3 Data Cleaning as a Process Missing values, noise, and inconsistencies contribute to inaccurate data. So far, we have looked at techniques for handling missing data and ... 97 2.7 Summary 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 preprocessing includes data cleaning,...
Ngày tải lên: 08/08/2014, 18:22
Data Mining Concepts and Techniques phần 3 docx
... processing, and data mining. We also introduce on-line analytical mining (OLAM), a powerful paradigm that integrates 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 Overview 3.5 From Data Warehousing to Data Mining “How do data warehousing and OLAP relate to data mining? ” In this section, we study the usage of data warehousing...
Ngày tải lên: 08/08/2014, 18:22
Data Mining Concepts and Techniques phần 4 potx
... include data cube–based data aggregation and attribute- oriented induction. From a data analysis point of view, data generalization is a form of descriptive data mining. Descriptive data mining ... Cercone, and Han [CCH91] and further extended by Han, Cai, and Cercone [HCC93], Han and Fu [HF96], Carter and Hamilton [CH98], and Han, Nishio, Kawano, and Wang [HNKW98]. 4.3 Attribute-Oriented Induction—An ... mining describes data in a concise and summarative manner and presents interesting general properties of the data. This is different from predic- tive data mining, which analyzes data in order to...
Ngày tải lên: 08/08/2014, 18:22
Data Mining Concepts and Techniques phần 5 ppt
... R1, R1: IF age = youth AND student = yes THEN buys computer = yes. The“IF”-part(or left-hand side) of a rule isknown astheruleantecedentorprecondition. The “THEN”-part (or right-hand side) isthe rule ... scalability. While both SLIQandSPRINThandle disk-resident data sets thatare too large to fit into memory, the scalabilityof SLIQ islimited by the useof its memory-residentdatastructure. SPRINT removes ... even for real-world data. RainForest has techniques, however, for handling the case where the AVC-group does not fit in memory. RainForest can use any attribute selection measure and was shown to...
Ngày tải lên: 08/08/2014, 18:22
Data Mining Concepts and Techniques phần 6 ppt
... functions (Hanson and Burr [HB88]), dynamic adjustment of the network topology (Me´zard and Nadal [MN89], Fahlman and Lebiere [FL90], Le Cun, Denker, and Solla [LDS90], and Harp, Samad, and Guha ... data in preparation for classification and prediction can involve data cleaning to reduce noise or handle missing values, relevance analysis to remove irrelevant or redundant attributes, and data ... described in Preparata and Shamos [PS85]. References on case-based reasoning (CBR) include the texts Riesbeck and Schank [RS89] and Kolodner [Kol93], as well as Leake [Lea96] and Aamodt and Plazas [AP94]....
Ngày tải lên: 08/08/2014, 18:22
Oracle9i Data Mining Concepts Release 9.2.0.2 October 2002 Part No. A95961-02 Oracle9i Data
... faster than the viii Basic ODM Concepts 1-1 1 Basic 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 Server The Data Mining ... main components: ■ Oracle9i Data Mining API ■ Data Mining Server (DMS) 1.2.1 Oracle9i Data Mining API The Oracle9i Data Mining API is the component of Oracle9i Data Mining that allows users to...
Ngày tải lên: 06/11/2013, 01:15
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 Classifiers Examples: – 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-neighbor Voronoi Diagram © Tan,Steinbach, Kumar Introduction to Data Mining 38 Nearest-Neighbor Classifiers Requires ... 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...
Ngày tải lên: 15/03/2014, 09:20
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 Induction Greedy ... Tan,Steinbach, Kumar Introduction to Data Mining 3 Illustrating Classification Task © Tan,Steinbach, Kumar Introduction to Data Mining 13 Apply Model to Test Data Refund MarSt TaxInc YES NO NO NO Yes ... Attributes Training Data Model: Decision Tree © Tan,Steinbach, Kumar Introduction to Data Mining 8 Decision Tree Classification Task Decision Tree © Tan,Steinbach, Kumar Introduction to Data Mining 35...
Ngày tải lên: 15/03/2014, 09:20
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 Algorithms Lecture Notes for Chapter 6 Introduction to Data Mining by Tan, Steinbach, Kumar © Tan,Steinbach, Kumar Introduction to Data ... to Data Mining 49 Effect of Support Distribution Many real data sets have skewed support distribution Support 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 Comparisons Candidate counting: – Scan the database of transactions...
Ngày tải lên: 15/03/2014, 09:20
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 Attributes Potential 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 hypothesis 2 2 2 1 2 1 ' n s n s Z + ∆−− = µµ © Tan,Steinbach, Kumar Introduction to Data Mining 3 Handling Categorical Attributes Transform...
Ngày tải lên: 15/03/2014, 09:20
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 Clusters Basic K-means ... Tan,Steinbach, Kumar Introduction to Data Mining 42 Limitations of K-means: Non-globular Shapes Original Points K-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 Ambiguous How many clusters? Four Clusters Two Clusters Six Clusters © Tan,Steinbach, Kumar Introduction to Data Mining 41 Limitations...
Ngày tải lên: 15/03/2014, 09:20
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: Steps Preprocessing Step: Represent the Data by a Graph – Given...
Ngày tải lên: 15/03/2014, 09:20
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...
Ngày tải lên: 07/04/2014, 11:16