introduction to data acquisition

Introduction to Data Access

Introduction to Data Access

... expect It’s up to you, as a developer, to decide how you expect them to occur and to use transactions to meet your goals CHAPTER ■ INTRODUCTION TO DATA ACCESS • Network connections to database systems ... important to fix These categories apply whenever you write data- access code To our knowledge, all data- access tools available today can be affected by any of these categories Database Resources Data- access ... invoices to its work The database stores all members and all invoices It must be possible to get a list of all CHAPTER ■ INTRODUCTION TO DATA ACCESS invoices per member, which means the database...

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Tài liệu A Concise Introduction to Data Compression- P1 pdf

Tài liệu A Concise Introduction to Data Compression- P1 pdf

... The third factor that affects the storage and transmission of data is security Generally, we not want our data transmissions to be intercepted, copied, and read on their way Even data saved on ... specific type of data The goal of the book is to introduce the reader to the chief approaches, methods, and techniques that are currently employed to compress data The main aim is to start with ... www.verypdf.com to remove this watermark 1 Approaches to Compression How can a given a data file be compressed? Compression amounts to eliminating the redundancy in the data, so the first step is to find...

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Tài liệu A Concise Introduction to Data Compression- P2 ppt

Tài liệu A Concise Introduction to Data Compression- P2 ppt

... determines whether it is a token or raw data A token is used to obtain data from the dictionary and write it on the output Raw data is output as is The decoder does not have to parse the input in ... Compare X to its successors in the tree (from left to right and bottom to top) If the immediate successor has frequency F + or greater, the nodes are still in sorted order and there is no need to change ... encoder has to use a buffer Bits of the compressed data are entered into the buffer as they are being generated and are moved out of it at a constant rate, to be transmitted It is easy to see intuitively...

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Tài liệu A Concise Introduction to Data Compression- P3 pptx

Tài liệu A Concise Introduction to Data Compression- P3 pptx

... order to remove ambiguity, the term “edoc” is used here to refer to them Each edoc is converted to a prefix code that’s output The first table allocates edocs through 255 to the literals, edoc 256 to ... frequency It is also possible to modify this transform to conserve the energy of the data vector All that’s needed is to multiply the transformation matrix W by the scale factor 1/2 Thus, the product ... statistical model of the data They are based on the fact that the data files that are of interest to us, the files we want to compress and keep for later use, are not random A typical data file features...

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Tài liệu A Concise Introduction to Data Compression- P4 pptx

Tài liệu A Concise Introduction to Data Compression- P4 pptx

... wavelet transform is the tool used in practice to analyze digital data and compress it The wavelet transform is a tool that cuts up data or functions or operators into different frequency components, ... compressed in a single left -to- right, top -to- bottom scan; (b) progressive mode where the image is compressed in multiple blocks (known as “scans”) to be viewed from coarse to fine detail; (c) lossless ... DCT when applied to a continuous-tone image and to a discrete-tone image We start with the highly correlated pattern of Table 5.10 This is an idealized example of a continuous-tone image, since...

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Tài liệu A Concise Introduction to Data Compression- P5 docx

Tài liệu A Concise Introduction to Data Compression- P5 docx

... computer users long to realize that a computer can also store and process nonnumeric data The term “multimedia,” which became popular in the 1990s, refers to the ability to digitize, store, and manipulate ... is then applied in the same manner to three of the 16 subbands, decomposing each into 16 smaller subbands The last step is to decompose the top-left subband into four smaller ones 11 12 13 14 15 ... audio file, we often want to listen to it while it is decompressed (in fact, we decompress it only in order to listen to it) This is why audio compression methods tend to be asymmetric The encoder...

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Tài liệu A Concise Introduction to Data Compression- P6 pptx

Tài liệu A Concise Introduction to Data Compression- P6 pptx

... method to “predict” (to assign probabilities to) the data to be compressed This concept is important in statistical data compression When a statistical method is used, a model for the data has to ... Shannon–Fano constructs its codes top to bottom (from the leftmost to the rightmost bits), while Huffman constructs a code tree from the bottom up (builds the codes from right to left) (See also Shannon–Fano ... save pieces of the data in a “dictionary” data structure If a string of new data is identical to a piece that is already saved in the dictionary, a pointer to that piece is output to the compressed...

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Tài liệu A Concise Introduction to Data Compression- P7 doc

Tài liệu A Concise Introduction to Data Compression- P7 doc

... method to “predict” (to assign probabilities to) the data to be compressed This concept is important in statistical data compression When a statistical method is used, a model for the data has to ... Shannon–Fano constructs its codes top to bottom (from the leftmost to the rightmost bits), while Huffman constructs a code tree from the bottom up (builds the codes from right to left) (See also Shannon–Fano ... save pieces of the data in a “dictionary” data structure If a string of new data is identical to a piece that is already saved in the dictionary, a pointer to that piece is output to the compressed...

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Tài liệu Module 1: Introduction to Data Warehousing and OLAP pptx

Tài liệu Module 1: Introduction to Data Warehousing and OLAP pptx

... Module 1: Introduction to Data Warehousing and OLAP ! Organizes data into non-volatile, subject-specific groups A data warehouse stores data as non-volatile, subject-oriented data sets A data warehouse ... as their data sources Customer_Dim Customer_Dim ShipperKey ShipperKey ShipperID ShipperID CustomerKey CustomerKey CustomerID CustomerID To facilitate data retrieval and analysis, a data warehouse ... Storage Data Storage Relational Relational Data Structure Data Structure N-dimensional N-dimensional Data structure Data structure Data Content Data Content Detailed and Detailed and Summarized Data...

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Tài liệu Module 17: Introduction to Data Mining pptx

Tài liệu Module 17: Introduction to Data Mining pptx

... 17: Introduction to Data Mining Data Mining Models Topic Objective To describe different data mining models and how they apply to data analysis ! Analysis Services Models Lead-in A variety of data ... Module 17: Introduction to Data Mining 19 Selecting Training Data Topic Objective To review the meaning of training data and demonstrate how to select training data Lead-in What is training data? ... Introduction to Data Mining Overview Topic Objective To provide an overview of the module topics and objectives ! Introducing Data Mining Lead-in ! Training a Data Mining Model ! Building a Data...

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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

... better, customized services for an edge (e.g in Customer Relationship Management) © Tan,Steinbach, Kumar Introduction to Data Mining Why Mine Data? Scientific Viewpoint Data collected and stored at ... analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns © Tan,Steinbach, Kumar Introduction to Data Mining What is (not) Data Mining? ... © Tan,Steinbach, Kumar Total Articles 555 354 278 Introduction to Data Mining 19 Clustering of S&P 500 Stock Data Observe Stock Movements every day Clustering points: Stock-{UP/DOWN} Similarity...

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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

... Kumar Introduction to Data Mining Types of data sets Record – Data Matrix – Document Data – Transaction Data Graph – World Wide Web – Molecular Structures Ordered – Spatial Data – Temporal Data ... Tan,Steinbach, Kumar Introduction to Data Mining 19 Ordered Data Spatio-Temporal Data Average Monthly Temperature of land and ocean © Tan,Steinbach, Kumar Introduction to Data Mining 20 Data Quality ... and Dense Linear System Solvers Introduction to Data Mining 16 Chemical Data Benzene Molecule: C6H6 © Tan,Steinbach, Kumar Introduction to Data Mining 17 Ordered Data Sequences of transactions...

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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

... object Introduction to Data Mining separate face becomes a Star Plots for Iris Data Setosa Versicolour Virginica © Tan,Steinbach, Kumar Introduction to Data Mining 29 Chernoff Faces for Iris Data ... Tan,Steinbach, Kumar Introduction to Data Mining 35 OLAP Operations: Data Cube The key operation of a OLAP is the formation of a data cube A data cube is a multidimensional representation of data, together ... two slides © Tan,Steinbach, Kumar Introduction to Data Mining 23 Visualization of the Iris Data Matrix standard deviation © Tan,Steinbach, Kumar Introduction to Data Mining 24 Visualization of...

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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

... same data! 10 © Tan,Steinbach, Kumar Introduction to Data Mining Decision Tree Classification Task Decision Tree © Tan,Steinbach, Kumar Introduction to Data Mining Apply Model to Test Data Test Data ... that belong to more than one class, use an attribute test to split the data into smaller subsets Recursively apply the procedure to each subset © Tan,Steinbach, Kumar Introduction to Data Mining ... Determine how to split the records • How to specify the attribute test condition? • How to determine the best split? – Determine when to stop splitting © Tan,Steinbach, Kumar Introduction to Data Mining...

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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

... (2) and (3) until stopping criterion is met © Tan,Steinbach, Kumar Introduction to Data Mining 14 Example of Sequential Covering (ii) Step © Tan,Steinbach, Kumar Introduction to Data Mining 15 Example ... Step Introduction to Data Mining 16 Aspects of Sequential Covering Rule Growing Instance Elimination Rule Evaluation Stopping Criterion Rule Pruning © Tan,Steinbach, Kumar Introduction to Data ... that have the k smallest distance to x © Tan,Steinbach, Kumar Introduction to Data Mining 39 nearest-neighbor Voronoi Diagram © Tan,Steinbach, Kumar Introduction to Data Mining 40 Nearest Neighbor...

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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

... Pointer to projected database of its ancestor node – Bitvector containing information about which transactions in the projected database contain the itemset © Tan,Steinbach, Kumar Introduction to Data ... support © Tan,Steinbach, Kumar Introduction to Data Mining 12 Illustrating Apriori Principle Found to be Infrequent Pruned supersets © Tan,Steinbach, Kumar Introduction to Data Mining 13 Illustrating ... (NM) – Use efficient data structures to store the candidates or transactions – No need to match every candidate against every transaction © Tan,Steinbach, Kumar Introduction to Data Mining 11 Reducing...

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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

... 7, 8, 1, 1, 1, 8, Introduction to Data Mining 26 Examples of Sequence Data Sequence Database Sequence Element (Transaction) Event (Item) Customer Purchase history of a given customer A set of items ... need to perform more passes over the data – May miss some potentially interesting cross© Tan,Steinbach, Kumar Introduction to Data Mining 25 level association patterns Sequence Data Sequence Database: ... Kumar Introduction to Data Mining 20 Multi-level Association Rules Food Electronics Bread Computers Milk Wheat Skim White Foremost © Tan,Steinbach, Kumar 2% Desktop Kemps Introduction to Data...

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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

... Tan,Steinbach, Kumar Introduction to Data Mining Notion of a Cluster can be Ambiguous How many clusters? Six Clusters Two Clusters Four Clusters © Tan,Steinbach, Kumar Introduction to Data Mining Types ... hierarchical tree © Tan,Steinbach, Kumar Introduction to Data Mining Partitional Clustering Original Points © Tan,Steinbach, Kumar A Partitional Clustering Introduction to Data Mining Hierarchical Clustering ... Tan,Steinbach, Kumar Introduction to Data Mining 18 Clustering Algorithms K-means and its variants Hierarchical clustering Density-based clustering © Tan,Steinbach, Kumar Introduction to Data Mining 19...

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Data Mining Cluster Analysis: Advanced Concepts and Algorithms Lecture Notes for Chapter 9 Introduction to Data Mining pot

Data Mining Cluster Analysis: Advanced Concepts and Algorithms Lecture Notes for Chapter 9 Introduction to Data Mining pot

... Kumar Introduction to Data Mining 17 Experimental Results: CHAMELEON © Tan,Steinbach, Kumar Introduction to Data Mining 18 Experimental Results: CHAMELEON © Tan,Steinbach, Kumar Introduction to Data ... (c) and (d) Introduction to Data Mining 13 Chameleon: Clustering Using Dynamic Modeling Adapt to the characteristics of the data set to find the natural clusters Use a dynamic model to measure ... Rastogi, Shim © Tan,Steinbach, Kumar Introduction to Data Mining Experimental Results: CURE (centroid) (single link) Picture from CURE, Guha, Rastogi, Shim © Tan,Steinbach, Kumar Introduction to...

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discovering knowledge in data an introduction to data mining

discovering knowledge in data an introduction to data mining

... 7.3 Eulerian Walks and Hamiltonian Cycles 135 Trees 8.1 How to Define Trees 8.2 How to Grow Trees 8.3 How to Count Trees? 8.4 How to Store Trees 8.5 The ... finally get to a node that does not represent a question, but contains a listing of the elements of S Thus to select a subset corresponds to walking down this diagram from the top to the bottom There ... logicians who are to blame In fact, you will find this quite natural and handy after a while.) There are many ways to order the subsets of a set to form a list A fairly natural thing to is to start with...

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