5 data mining scoring engine installation

... Trang 1DATA MININGLECTURE 5 Sequential Pattern Mining Trang 2Outline • Sequence database • Methods for sequential pattern mining • GSP • SPADE • PrefixSpan Trang ... Create projected databases and pursue (follow) recursive mining over bi-level projected databases Trang 34Speed-up by Pseudo-projection34 ` repeatedly in recursive projected databases collecting ... 2001 • A vertical format sequential pattern mining method • A sequence database is mapped to a large set of Item: <SID, EID> • Sequential pattern mining is performed by – growing the subsequences

Ngày tải lên: 08/11/2022, 14:02

... determining density just by looking at the number of points in a given area, particularly if in some places the given volume only has one data point, or even no data points, in it If enough data ... mean density of the data points depends on the number of data points present and the size of the space The number of dimensions fixes unit state space volume, but the number of data points in that ... cure! The data survey, in part, examines the manifold carefully and should report the location and extent of any such areas in the data At least when modeling in such an area of the data, the

Ngày tải lên: 08/11/2013, 02:15

... of the data representation in state space Translating the information discovered there into insights about the data, and the objects the data represents, forms an important part of the data survey ... normalization methods have anything in common with putting data into the multitable structures called “normal form” in a database, data warehouse, or other data repository.) During the process of manipulation, ... prepared for surveying and mining Trang 14Chapter 7: Normalizing and Redistributing VariablesOverview From this point on in preparing the data, all of the variables in a data set have a numerical

Ngày tải lên: 08/11/2013, 02:15

... to the information content of the data set Yet it still leaves some information exposed for the mining tools to use when values outside those within the sample data set are encountered Trang 37.2 ... For instance, one such tool for a particular data set could, when fine-tuned and adjusted, do just as well with unprepared data as with prepared data The difference was that it took over three ... of the data survey However, it is during the data preparation process that they are first “discovered.” 7.2.4 Modified Distributions When the distributions are adjusted, what changes? The data

Ngày tải lên: 08/11/2013, 02:15

... statistical data learning and mining techniques tothe multimedia domain are also provided in this chapter.Data mining is defined as discovering hidden information in a data set.Like data mining in ... searching the data The model in data mining can be either predictive or descriptive in nature Apredictive model makes a prediction about values of data using known resultsfound from different data sources ... characteristics of the data being examined Typical datamining algorithms can be characterized as consisting of three components: • Model: The purpose of the algorithm is to fit a model to the data • Preference:

Ngày tải lên: 10/12/2013, 09:15

... compressed data are properly indexed, it may improve the performance of mining data in the compressed large database as well This is particularly useful when interactivity is involved with a data mining ... very important to develop search engines in other multimedia datatypes, especially for image datatypes Mining of data in the imagery do-main is a challenge Image mining [33] deals with the extraction ... preprocessing task in data mining Need for reduced representation of data is crucial for the success of very large multimedia database applications and the associated Trang 2economical usage of data storage

Ngày tải lên: 13/12/2013, 01:15

... Introduction to Data Mining 11.1 Introduction 11.2 Knowledge Discovery and Data Mining 51.3 Data Compression 101.4 Information Retrieval 121.5 Text Mining 141.6 Web Mining 151.7 Image Mining 161.8 ... Algorithms in Data Mining 702.5.1 Regression 712.5.2 Association rules 712.6 Role of Rough Sets in Data Mining 722.7 Role of Wavelets in Data Mining 732.8 Role of Hybridizations in Data Mining 742.9 ... this age of multimedia data exploration,data mining should no longer be restricted to the mining of knowledge fromlarge volumes of high-dimensional datasets in traditional databases only Re-searchers

Ngày tải lên: 13/12/2013, 01:15

... Describing Series Data Series data differs from the forms of data so far discussed mainly in the way in which the data enfolds the information The main difference is that the ordering of the data carries ... main reason that series data has to be prepared differently from nonseries data There is a large difference between preparing data for modeling and actually modeling the data This book focuses ... a series data set so that it can be accurately and completely characterized 2 Find methods for manipulating the unique features of series data to expose the information content to mining tools

Ngày tải lên: 15/12/2013, 13:15

... drawback is that the contribution of each data point is equal to that of all the other data points in the weighting period It may be that the more distant past data values are less relevant than more ... some specific number of contiguous data points It corresponds to the lag distance mentioned before The only difference between a window and a lag is that the data in a window is manipulated in ... in some way, say, changed in order A lag implies that the data is not manipulated As the window moves through the series, the oldest data point is discarded, and a new one is Trang 10added When

Ngày tải lên: 15/12/2013, 13:15

... needed function in the training data set, the function improves its fit with the test data too When the function learned in the training data begins to fit the test data less well, training is halted ... typically refer to these as data reduction methods.) Principal components analysis is a technique used for concentrating variability in a data set Each of the dimensions in a data set possesses a variability ... Using MDS to collapse a large data set can be highly computationally intensive In Chapter 6, MDS was used in the numeration of alpha labels When using MDS to reduce data set dimensionality, instead

Ngày tải lên: 15/12/2013, 13:15

... far as data preparation for data mining is concerned, the journey ends here However, the data is still unmined The ultimate purpose of preparing data is to gain understanding of what the data “means” ... introduced Such data has a perspective. When mining perspectival data sets, it is very important to use nonperspectival test and evaluation sets With the best of intentions, the mining data has been ... The prepared data set still has to be used How is this data used? The last two chapters look not at preparing data, but at surveying and using prepared data Trang 9Chapter 11: The Data SurveyOverview

Ngày tải lên: 15/12/2013, 13:15

... 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 of Sequential Covering… R1 R1 ... 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 Mining 17 ... Kumar Introduction to Data Mining 20 Rule Evaluation Metrics: – Accuracy nc = n nc + = – Laplace n +k nc + kp = n +k – M-estimate © Tan,Steinbach, Kumar Introduction to Data Mining n : Number of...

Ngày tải lên: 15/03/2014, 09:20

... assuming a small data size Recent data mining research has built on such work, developing scalable classification and prediction techniques capable of handling large disk-resident data In this chapter, ... to extract models describing important data classes or to predict future data trends Such analysis can help provide us with a better understanding of the data at large Whereas classification predicts ... “safe” or “risky” for the loan application data; “yes” or “no” for the marketing data; or “treatment A,” “treatment B,” or “treatment C” for the medical data These categories can be represented...

Ngày tải lên: 08/08/2014, 18:22

... perform preliminary data scanning and analysis as a first step to data mining It shows how both the data mining model and the OLAP cube model are different representations of the same data source and ... implementation of data mining in SQL Server 2000 The data mining capabilities provided in SQL Server 2000 are described in the following sections 5.6 Building the analysis view for data mining 5.6.1 ... data mining view of the data are the same as creating a dimensional view of the data Figure 5.32 Analysis Manager startup sequence Chapter 142 5.9 Figure 5.33 Creating the mining model The Data Mining...

Ngày tải lên: 08/08/2014, 22:20

... that work by agglomeration In these methods, we start out with each data point forming its own 73 Knowledge Discovery and Data Mining cluster and gradually merge clusters until all points have ... cluster and the rest of the database will go a long way towards explaining what makes the cluster special As for the second question, that is what all the other data mining techniques are for! ... a database have been mapped to points in space, automatic cluster detection is really quite simplea little geometry, some vector means, and that’s all! The problem, of course, is that the databases...

Ngày tải lên: 14/08/2014, 02:21

... trong qui trình KDD Pattern Evaluation Data mining Task relevant data Data warehouse Data cleaning Knowledge Data integration selection Mục đích KTDL Data Mining Descriptive Predictive Classification ... Environment • Subject = Customer • Data Warehouse Biến thời gian • Time • Data • 01/97 Data for January • • 02/97 Data for February • • 03/97 Data for March • • Data • Warehouse Ổn Định • Là lưu ... Nội Dung • Kho liệu (Data warehouse) • Khai thác liệu (Data mining) – Giới thiệu – Giới thiệu – Qui trình khám phá tri thức – Định nghĩa – DW - Traditional Database – Luật kết hợp – Mục...

Ngày tải lên: 18/01/2013, 16:15

... lý liệu Pattern Evaluation/ Presentation Data Mining Patterns Task-relevant Data Data Warehouse Data Cleaning Selection/Transformation Data Integration Data Sources 2.1 Tổng quan giai đoạn tiền ... ZhaoHui Tang, Jamie MacLennan, Data Mining with SQL Server 2005”, Wiley Publishing, 2005  [6] Oracle, Data Mining Concepts”, B28129-01, 2008  [7] Oracle, Data Mining Application Developer’s ... Micheline Kamber, Data Mining: Concepts and Techniques”, Second Edition, Morgan Kaufmann Publishers, 2006  [2] David Hand, Heikki Mannila, Padhraic Smyth, “Principles of Data Mining , MIT Press,...

Ngày tải lên: 23/01/2013, 22:17

... Name Chỉ định tên worksheet mà bạn chọn vào Nhấp vào nút ( ) để chọn từ danh sách worksheet sẵn Data range: Bạn nhập liệu bắt đầu với hàng không trống với phạm vi rõ ràng: • First non-blank row: ... thị tên theo lệnh thực hiện, bạn đặt tên lại cho lệnh “phan cum” hay tùy ý bạn Use partitioned data: Sử dụng liệu phân vùng Nếu trước liệu bạn thực lệnh Partition Number of clusters: Xác định ... Kinh Tế TPHCM 23 Hình 5.3: Bảng tùy chọn neural Model: Model name: Tên mô hình Use partitioned data: Sử dụng liệu phân vùng Method: Phương pháp Có sáu phương pháp để xây dựng mô hình mạng thần...

Ngày tải lên: 17/02/2013, 16:08

... small dataset, need all observations to estimate parameters of interest • Data mining – loads of data, can afford “holdout sample” • Variation: n-fold cross validation – Randomly divide data into ... Testing joint importance versus individual significance Two engine plane can still fly if engine #1 fails Two engine plane can still fly if engine #2 fails Neither is critical individually Jointly ... April 2012 Data Mining - What is it? • • • • Large datasets Fast methods Not significance testing Topics – Trees (recursive splitting)...

Ngày tải lên: 04/03/2013, 14:32