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hash-based approach to data mining

hash-based approach to data mining

hash-based approach to data mining

... said to be a good method to implement over different types of data in variant size. Hash-Based Approach to Data Mining 11 CHAPTER 2: Algorithms using hash- based approach to ... hash function to divide the original set into subsets. By this action, we will not waste too much time doing useless thing. Our thesis with the subject Hash-based approach to data mining will ... the database. Table 1: Transaction database TID Items 100 ABCD 200 ABCDF 300 BCDE 400 ABCDF 500 ABEF Hash-Based Approach to Data Mining 9 Figure 1: An example to get...
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Tài liệu Module 17: Introduction to Data Mining pptx

Tài liệu Module 17: Introduction to Data Mining pptx

... a Data Mining Model Mining ModelDMEngine Data To PredictDMEnginePredicted Data Training Data Mining Model To create a model, you must assemble a set of data where the attributes to ... applied to future data to predict outcomes or classify data. Topic Objective To explain the methodology for creating a mining model and to define terminology. Lead-in When creating a data mining ... are known. Such a data set is called the training data. During the training process, data is inserted into the data mining model. The data mining model analyzes the training data and looks for...
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Data Mining: Introduction Lecture Notes for Chapter 1 Introduction to Data Mining ppt

Data Mining: Introduction Lecture Notes for Chapter 1 Introduction to Data Mining ppt

... Data Mining: IntroductionLecture Notes for Chapter 1Introduction to Data Mining byTan, Steinbach, Kumar© Tan,Steinbach, Kumar Introduction to Data Mining 20 Clustering of S&P 500 Stock Data Discovered ... Introduction to Data Mining 29 Challenges of Data Mining ScalabilityDimensionalityComplex and Heterogeneous Data Data Quality Data Ownership and DistributionPrivacy PreservationStreaming Data © ... a customer is likely to be lost to a competitor.– Approach: •Use detailed record of transactions with each of the past and present customers, to find attributes.–How often the customer...
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Data Mining: Data Lecture Notes for Chapter 2 Introduction to Data Mining potx

Data Mining: Data Lecture Notes for Chapter 2 Introduction to Data Mining potx

... Introduction to Data Mining 1 Data Mining: Data Lecture Notes for Chapter 2Introduction to Data Mining byTan, Steinbach, Kumar© Tan,Steinbach, Kumar Introduction to Data Mining 20 Ordered Data '&Average ... Introduction to Data Mining 10 Types of data sets – Data Matrix–Document Data –Transaction Data –World Wide Web–Molecular Structures!–Spatial Data –Temporal Data –Sequential ... Solvers© Tan,Steinbach, Kumar Introduction to Data Mining 17 Chemical Data /0,1+1© Tan,Steinbach, Kumar Introduction to Data Mining 18 Ordered Data '2An...
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Data Mining: Exploring Data Lecture Notes for Chapter 3 Introduction to Data Mining potx

Data Mining: Exploring Data Lecture Notes for Chapter 3 Introduction to Data Mining potx

... Introduction to Data Mining 1 Data Mining: Exploring Data Lecture Notes for Chapter 3Introduction to Data Mining byTan, Steinbach, Kumar© Tan,Steinbach, Kumar Introduction to Data Mining 20 Scatter ... ability to distinguish faces© Tan,Steinbach, Kumar Introduction to Data Mining 29 Star Plots for Iris Data SetosaVersicolourVirginica© Tan,Steinbach, Kumar Introduction to Data Mining 2 ... Introduction to Data Mining 22 Contour Plot Example: SST Dec, 1998Celsius© Tan,Steinbach, Kumar Introduction to Data Mining 23 Visualization Techniques: Matrix PlotsMatrix plots –Can plot the data...
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Data Mining Classification: Basic Concepts, Decision Trees, and Model Evaluation Lecture Notes for Chapter 4 Introduction to Data Mining pptx

Data Mining Classification: Basic Concepts, Decision Trees, and Model Evaluation Lecture Notes for Chapter 4 Introduction to Data Mining pptx

... Test Data Assign Cheat to “No”© Tan,Steinbach, Kumar Introduction to Data Mining 15 Decision Tree Classification TaskDecision Tree© Tan,Steinbach, Kumar Introduction to Data Mining 16 ... to more than one class, use an attribute test to split the data into smaller subsets. Recursively apply the procedure to each subset.Dt?© Tan,Steinbach, Kumar Introduction to Data Mining ... for Chapter 4Introduction to Data Mining byTan, Steinbach, Kumar© Tan,Steinbach, Kumar Introduction to Data Mining 1 © Tan,Steinbach, Kumar Introduction to Data Mining 20 Tree InductionGreedy...
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Data Mining Classification: Alternative Techniques - Lecture Notes for Chapter 5 Introduction to Data Mining pdf

Data Mining Classification: Alternative Techniques - Lecture Notes for Chapter 5 Introduction to Data Mining pdf

... covered by R1 Data Mining Classification: Alternative TechniquesLecture Notes for Chapter 5Introduction to Data Mining byTan, Steinbach, Kumar© Tan,Steinbach, Kumar Introduction to Data Mining ... Introduction to Data Mining 17 Aspects of Sequential CoveringRule GrowingInstance EliminationRule EvaluationStopping CriterionRule Pruning© Tan,Steinbach, Kumar Introduction to Data Mining 18 ... (3) until stopping criterion is met © Tan,Steinbach, Kumar Introduction to Data Mining 15 Example of Sequential Covering(ii) Step 1© Tan,Steinbach, Kumar Introduction to Data Mining 16 Example...
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Data Mining Association Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 6 Introduction to Data Mining pdf

Data Mining Association Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 6 Introduction to Data Mining pdf

... 8 Data Mining Association Analysis: Basic Concepts and AlgorithmsLecture Notes for Chapter 6Introduction to Data Mining byTan, Steinbach, Kumar© Tan,Steinbach, Kumar Introduction to Data ... Kumar Introduction to Data Mining 16 Reducing Number of ComparisonsCandidate counting:–Scan the database of transactions to determine the support of each candidate itemset– To reduce the number ... Tan,Steinbach, Kumar Introduction to Data Mining 21 Subset OperationGiven a transaction t, what are the possible subsets of size 3?© Tan,Steinbach, Kumar Introduction to Data Mining 22 Subset Operation...
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Data Mining Association Rules: Advanced Concepts and Algorithms Lecture Notes for Chapter 7 Introduction to Data Mining docx

Data Mining Association Rules: Advanced Concepts and Algorithms Lecture Notes for Chapter 7 Introduction to Data Mining docx

... 0.33 Data Mining Association Rules: Advanced Concepts and AlgorithmsLecture Notes for Chapter 7Introduction to Data Mining byTan, Steinbach, Kumar© Tan,Steinbach, Kumar Introduction to Data Mining ... 7Sequence Database:© Tan,Steinbach, Kumar Introduction to Data Mining 27 Examples of Sequence Data Sequence DatabaseSequence Element (Transaction)Event(Item)Customer Purchase history of ... we need to perform more passes over the data –May miss some potentially interesting cross-level association patterns© Tan,Steinbach, Kumar Introduction to Data Mining 26 Sequence Data Object...
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Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining pot

Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining pot

... for Chapter 8Introduction to Data Mining byTan, Steinbach, Kumar© Tan,Steinbach, Kumar Introduction to Data Mining 1 © Tan,Steinbach, Kumar Introduction to Data Mining 20 K-means ClusteringPartitional ... global objective function approach is to fit the data to a parameterized model. • Parameters for the model are determined from the data. • Mixture models assume that the data is a ‘mixture' ... ××m1m2m10919)35.4(2)5.13(21)5.45()5.44()5.12()5.11(222222=+==−×+−×==−+−+−+−=TotalBSSWSSK=2 clusters:100100)33(410)35()34()32()31(22222=+==−×==−+−+−+−=TotalBSSWSSK=1 cluster:© Tan,Steinbach, Kumar Introduction to Data Mining 10 Types...
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