... small dataset, need all observations to estimate parameters of interest • Datamining – loads of data, can afford “holdout sample” • Variation: n-fold cross validation – Randomly divide data into ... 2(p-value) to 0.05 Multiple testing • • • • • • 50 different BPs in data, m=49 ways to split Multiply p-value by 49 Bonferroni – original idea Kass – apply to datamining (trees) Stop splitting ... April 2012 DataMining - What is it? • • • • Large datasets Fast methods Not significance testing Topics – Trees (recursive splitting) – Logistic...
... online analytical mining provide users with the flexibility to select desired datamining functions and swap datamining tasks dynamically 13 TERMINOLOGIES DataMiningDataMiningDatamining is defined ... time DataMining Task Primitives We can specify a datamining task in the form of a datamining query This query is input to the system A datamining query is defined in terms of datamining ... About the TutorialDataMining is defined as the procedure of extracting information from huge sets of data In other words, we can say that datamining is mining knowledge from data The tutorial...
... “Necessity is the mother of invention” - DataMining đời hướng giải hữu hiệu cho câu hỏi vừa đặt Khá nhiều định nghĩa DataMining đề cập phần sau, nhiên tạm hiểu DataMining công nghệ tri thức giúp khai ... tương tự với từ Datamining Knowledge Mining (khai phá tri thức), knowledge extraction(chắt lọc tri thức), data/ patern analysis(phân tích liệu/mẫu), data archaeoloogy (khảo cổ liệu), datadredging(nạo ... TỔNG QUAN VỀ KHAI PHÁ DỮ LIỆU - DATAMINING 1.Khai phá liệu gì? Khai phá liệu (datamining) định nghĩa trình chắt lọc hay khai phá tri thức từ lượng lớn liệu Thuật ngữ Dataming ám việc tìm kiếm tập...
... Preface Introduction 1.1 Data and Knowledge 1.2 Knowledge Discovery and Data 1.2.1 The KDD Process 1.2.2 DataMining Tasks 1.2.3 DataMining Methods 1.3 Graphical Models 1.4 Outline ... source of information for basically all topics related to datamining and knowledge discovery in databases Another web site well worth visiting for information about datamining and knowledge discovery ... discovery is: http://www.dmoz.org/Computers/Software/Databases /Data Mining/ 10 1.3 CHAPTER INTRODUCTION Graphical Models This book deals with two datamining tasks, namely dependence analysis and classification...
... trong qui trình KDD Pattern Evaluation Datamining Task relevant dataData warehouse Data cleaning Knowledge Data integration selection Mục đích KTDL DataMining 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...
... lý liệu Pattern Evaluation/ Presentation DataMining Patterns Task-relevant DataData Warehouse Data Cleaning Selection/Transformation Data Integration Data Sources 2.1 Tổng quan giai đoạn tiền ... ZhaoHui Tang, Jamie MacLennan, DataMining with SQL Server 2005”, Wiley Publishing, 2005 [6] Oracle, DataMining Concepts”, B28129-01, 2008 [7] Oracle, DataMining 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 DataMining , MIT Press,...
... 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: ... Train,test and validation : thực hiện, kiểm tra xác nhận Training partition size : % mẫu để thực Testing partition size : % mẫu để kiểm tra Validation partition size : % mẫu để xác nhận Values ... 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...
... : Database : Direct Hashing and Pruning : Hash table of k-itemsets : Large itemsets k elements : Perfect Hashing and DB Pruning : Perfect Hashing and data Shrinking : Set-oriented mining : Database ... future Hash-Based Approach to DataMining CHAPTER 1: Introduction 1.1 Overview of finding association rules It is said that, we are being flooded in the data However, all data are in the form of strings, ... more scientists concern on searching for useful information (models, patterns) that is hidden in the database Through the work of data mining, we can discover knowledge – the combination of information,...
... drive data gathering and experimental planning, and to structure the databases and data warehouses BK is used to properly select the data, choose the datamining strategies, improve the datamining ... modern datamining methods in several important areas of medicine, covering classical datamining methods, elaborated approaches related to mining in EEG and ECG data, and methods related to mining ... their databases It results into numerous applications of various datamining tools and techniques The analyzed data are in different forms covering simple data matrices, complex relational databases,...
... BASED DATAMINING TECHNIQUES The objective of datamining is to extract valuable information from one’s data, to discover the ‘hidden gold’ In Decision Support Management terminology, datamining ... on data retention and data distillation Rule induction models (Figure 2) belong to the logical, pattern distillation based approaches of datamining These technologies extract patterns from data ... REFERENCES [1] Akeel Al-Attar, 1998, DataMining – Beyond Algorithms’, http://www.attar.com/tutor /mining. htm [2] Berry, J A Michael; Linoff, Gordon, 1997, DataMining Techniques: For Marketing,...
... of data representation 2.6.2 Building Data Dealing with Variables The data representation can usefully be looked at from two perspectives: as data and as a data set The terms data and data ... actual mining due to their limited data capacity and inability to handle certain types of operations needed in data preparation, data surveying, and data modeling For exploring small data sets, ... information is crucial to datamining It is the very substance enfolded within a data set for which the data set is being mined It is the reason to prepare the data set for mining to best expose...
... bias Determining data structure Building the PIE Surveying the data Modeling the data 3.3.1 Stage 1: Accessing the Data The starting point for any data preparation project is to locate the data This ... step.” Basicdata preparation requires three such steps: data discovery, data characterization, and data set assembly • Data discovery consists of discovering and actually locating the data to ... preparation activities Data Issue: Representative Samples A perennial problem is determining how much data is needed for modeling One tenet of datamining is “all of the data, all of the time.”...
... additional information actually forms another data stream and enriches the original data Enrichment is the process of adding external data to the data set Note that data enhancement is sometimes confused ... example of enhancing the data No external data is added, but the existing data is restructured to be more useful in a particular situation Another form of data enhancement is data multiplication When ... understand the data Once the assay is completed, the miningdata set, or sets, can be assembled Given assembled data sets, much preparatory work still remains to be done before the data is in optimum...
... of the original data sample Random sampling does that If the original data set represents a biased sample, that is evaluated partly in the data assay (Chapter 4), again when the data set itself ... the alphas, but also for conducting the data survey and for addressing various problems and issues in datamining Becoming comfortable with the concept of data existing in state space yields insight ... most important metrics in both statistical analysis and datamining It is this concept of “level of confidence” that allows sampling of data sets to be made If the miner decided to use only a...
... import all dataminingmodels as well as other database objects Run DBMS _DATA_ MINING. import_model to import dataminingmodels only, either all models or selected models The Oracle Data Pump Utility ... schema including dataminingmodels will be exported When you run DBMS _DATA_ MINING. export_model with a NULL model filter, only dataminingmodels are exported To import dataminingmodels from a ... Oracle DataMining (ODM) embeds datamining within the Oracle database The data never leaves the database — the data, data preparation, model building, and model scoring results all remain in the database...
... accessibility of these Web sites xii Basic ODM Concepts Oracle9i DataMining (ODM) embeds datamining within the Oracle9i database The data never leaves the database — the data, data preparation, model building, ... Mining API s DataMining Server (DMS) 1.2.1 Oracle9i DataMining API The Oracle9i DataMining API is the component of Oracle9i DataMining that allows users to write Java programs that mine data ... of PMML models for Naive Bayes and Association Rules models PMML Oracle9i DataMining Concepts Oracle9i DataMining Components allows datamining applications to produce and consume models for...