introduction to data conversion chapter 12

... 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...

Ngày tải lên: 15/03/2014, 09:20

... 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...

Ngày tải lên: 15/03/2014, 09:20

... 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 ... percentile © Tan,Steinbach, Kumar Introduction to Data Mining 17 Example of Box Plots Box plots can be used to compare attributes © Tan,Steinbach, Kumar Introduction to Data Mining 18 Visualization...

Ngày tải lên: 15/03/2014, 09:20

... 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...

Ngày tải lên: 15/03/2014, 09:20

... (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...

Ngày tải lên: 15/03/2014, 09:20

... 245 C 123 AD 123 4 ABDE ACDE BCDE ABCDE Introduction to Data Mining 29 Maximal vs Closed Frequent Itemsets Minimum support = 124 123 A 12 124 AB 12 ABC 24 AC ABD ABE AE 345 D BC BD ACD 245 C 123 ... {A,B,C,D} © Tan,Steinbach, Kumar Introduction to Data Mining 28 Maximal vs Closed Itemsets TID Items ABC ABCD BCE ACDE DE Transaction Ids null 124 123 A 12 124 AB 12 24 AC ABC B AE 24 ABD ABE 2 ... 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...

Ngày tải lên: 15/03/2014, 09:20

... 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...

Ngày tải lên: 15/03/2014, 09:20

... 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...

Ngày tải lên: 15/03/2014, 09:20

... 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...

Ngày tải lên: 15/03/2014, 09:20

... 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 ... 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 ... java.sql.SQLException CHAPTER ■ INTRODUCTION TO DATA ACCESS Let’s look at how this code deals with the technical details of data access: • We’ve used a method, countTournamentRegistrations(), to encapsulate data- access...

Ngày tải lên: 05/10/2013, 04:20

... on www.verypdf.com to remove this watermark 1.2 Run-Length Encoding 43 Example: An 8-bit-deep grayscale bitmap that starts with 12, 12, 12, 12, 12, 12, 12, 12, 12, 35, 76, 112, 67, 87, 87, 87, ... three chapters They discuss the basic approaches to data compression and describe a few popular techniques and methods that are commonly used to compress data Chapter introduces the reader to the ... 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...

Ngày tải lên: 14/12/2013, 15:15

... 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 ... there is no need to store anything else or to add a new trie entry 11 Hash(f,278) → 276 Array location 276 is set to (278, 276, f) 12 Hash(a,102) → 274 Array location 274 is set to (102, 274, a)...

Ngày tải lên: 14/12/2013, 15:15

... sequence of CLs are compressed to 17, 112 , and 12 consecutive zeros in an SQ are compressed to 18, 012 The sequence of CLs is compressed in this way to a shorter sequence (to be termed SSQ) of integers ... −109.496, −185.206 When these coefficients are quantized to ( 120 , 170, −240, 125 , 120 , 9, −110, −185) and fed into the IDCT, the result is 12. 1249, 25.4974, −179.852, 208.237, 55.5898, 0.364874, ... 4.13b shows the same symbols sorted by count (a) (b) a1 11 a8 19 a2 12 a2 12 a3 12 a3 12 a4 a9 12 a5 a1 11 a6 a7 a8 a9 a10 19 12 a10 a5 a4 a7 a6 2 Table 4.13: A Ten-Symbol Alphabet With Counts...

Ngày tải lên: 14/12/2013, 15:15

... 12 16 12 12 14 14 14 14 14 14 14 14 (a) 12 12 12 12 12 16 12 12 12 12 12 12 12 16 12 12 12 12 12 12 12 16 12 12 12 12 12 12 12 16 12 12 12 12 12 12 12 16 12 12 13 12 13 12 13 12 13 12 13 12 15 ... of 12, except for a vertical line with pixel values of 14 and a horizontal line with pixel values of 16 12 12 12 12 12 16 12 12 12 12 12 12 12 16 12 12 12 12 12 12 12 16 12 12 12 12 12 12 12 ... www.verypdf.com to remove this watermark 5.5 The Discrete Cosine Transform 12 11 10 12 10 10 10 12 11 10 12 10 81 0 0 0 0 2 0 10 12 11 10 12 10 10 10 12 11 10 12 12 10 10 12 11 10 10 12 10 10 12 11 8 10 12...

Ngày tải lên: 14/12/2013, 15:15

... 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 17 10 16 18 ... 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 ... www.verypdf.com to remove this watermark 234 band range 0–50 50–95 95–140 140–235 235–330 330–420 420–560 560–660 660–800 Audio Compression band 10 11 12 13 14 15 16 17 range 800–940 940– 1125 1125 126 5 126 5–1500...

Ngày tải lên: 14/12/2013, 15:15

... 12 12 16 12 12 12 12 12 12 12 12 16 12 12 12 12 12 12 12 12 12 12 16 12 12 16 12 12 12 12 12 12 12 12 (a) 12 12 12 12 16 12 12 12 12 12 12 12 12 16 12 12 12 12 12 12 12 12 16 12 14 12 12 12 12 ... 14 12 12 12 12 12 12 12 12 14 14 12 12 12 12 12 12 12 12 12 12 12 14 12 14 12 12 14 12 14 12 12 (b) 0 0 0 0 4 0 0 0 0 4 0 0 0 0 4 13 12 12 12 0 13 13 12 12 2 0 12 13 13 12 2 12 12 13 13 0 2 (c) ... 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...

Ngày tải lên: 14/12/2013, 15:15

... 12 12 16 12 12 12 12 12 12 12 12 16 12 12 12 12 12 12 12 12 12 12 16 12 12 16 12 12 12 12 12 12 12 12 (a) 12 12 12 12 16 12 12 12 12 12 12 12 12 16 12 12 12 12 12 12 12 12 16 12 14 12 12 12 12 ... 14 12 12 12 12 12 12 12 12 14 14 12 12 12 12 12 12 12 12 12 12 12 14 12 14 12 12 14 12 14 12 12 (b) 0 0 0 0 4 0 0 0 0 4 0 0 0 0 4 13 12 12 12 0 13 13 12 12 2 0 12 13 13 12 2 12 12 13 13 0 2 (c) ... 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...

Ngày tải lên: 14/12/2013, 15:15

... 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...

Ngày tải lên: 21/12/2013, 19:15

... 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...

Ngày tải lên: 24/01/2014, 19:20

... of nonnegative integers up to 10: = 02 = 12 = 102 = + = 112 = 1002 = + = 1 012 = + = 1102 = + + = 1 112 = 10002 = + = 10 012 10 = + = 10102 (We put the subscript there to remind ourselves that we ... 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 ... append 0’s to the binary forms at their beginning, to make them all have the same length This way we get the following correspondence: ⇔ 02 ⇔ 12 ⇔ 102 ⇔ 112 ⇔ 1002 ⇔ 1 012 ⇔ 1102 ⇔ 1 112 ⇔ ⇔ ⇔ ⇔...

Ngày tải lên: 01/06/2014, 01:16