By Thearling K.
This white paper offers an creation to the fundamental applied sciences of information mining. Examples of ecocnomic purposes illustrate its relevance to cutting-edge company atmosphere in addition to a simple description of the way information warehouse architectures can evolve to carry the worth of information mining to finish clients.
Read or Download An Introduction to Data Mining PDF
Best organization and data processing books
Atomic and Molecular Data for Space Astronomy Needs, Analysis, and Availability
This can be a very priceless reference ebook for operating astronomers and astrophysicists. Forming the court cases of a up to date IAUmeeting the place the provision and the wishes of atomic andmolecular info have been mentioned, the papers released herediscuss current and deliberate tools for astronomicalspectroscopy from earth-orbiting satellites.
Used along the scholars' textual content, better nationwide Computing 2d variation , this pack deals a whole suite of lecturer source fabric and photocopiable handouts for the obligatory middle devices of the recent BTEC better Nationals in Computing and IT, together with the 4 middle devices for HNC, the 2 extra center devices required at HND, and the middle expert Unit 'Quality Systems', universal to either certificates and degree point.
- International Tables for Crystallography, Vol.G: Definition and Exchange of Crystallographic Data
- Compactness along the branch of semi-stable and unstable solutions for an elliptic problem with a singular nonlinearity
- Parametric survival models for interval-censored data with time-dependent covariates
- An Introduction to R: Notes on R: A Programming Environment for Data Analysis and Graphics
- Oracle 10G - Oracle Database 10G - SQL Fundamentals II - Student Guide
- Microsoft Office Excel 2007 Data Analysis: Your Visual Blueprint for Creating and Analyzing Data, Charts, and PivotTables
Extra resources for An Introduction to Data Mining
Sample text
Org) — XML based (DTD) — Java Data Mining API spec request (JSR-000073) — Oracle, Sun, IBM, … — Support for data mining APIs on J2EE platforms — Build, manage, and score models programmatically — OLE DB for Data Mining — Microsoft — Table based — Incorporates PMML — It takes more than an XML standard to get two applications to work together and make users more productive 73 Data Mining Moving into the Database — Oracle 9i — Darwin team works for the DB group, not applications — Microsoft SQL Server — IBM Intelligent Miner V7R1 — NCR Teraminer — Benefits: — Minimize data movement — One stop shopping — Negatives: — Limited to analytics provided by vendor — Other applications might not be able to access mining functionality — Data transformations still an issue > ETL a major part of data management 74 37 SAS Enterprise Miner — Market Leader for analytical software — Large market share (70% of statistical software market) > 30,000 customers > 25 years of experience — GUI support for the SEMMA process — Workflow management — Full suite of data mining techniques 75 Enterprise Miner Capabilities Regression Models K Nearest Neighbor Neural Networks Decision Trees Self Organized Maps Text Mining Sampling Outlier Filtering Assessment 76 38 Enterprise Miner User Interface 77 SPSS Clementine 78 39 Insightful Miner 79 Oracle Darwin 80 40 Angoss KnowledgeSTUDIO 81 Usability and Understandability — Results of the data mining process are often difficult to understand — Graphically interact with data and results — Let user ask questions (poke and prod) — Let user move through the data — Reveal the data at several levels of detail, from a broad overview to the fine structure — Build trust in the results 82 41 User Needs to Trust the Results — Many models – which one is best?
5B in 2005 — Depends on what you call “data mining” — Less of a focus towards applications as initially thought — Instead, tool vendors slowly expanding capabilities — Standardization — XML > CWM, PMML, GEML, Clinical Trial Data Model, … — Web services? — Integration — Between applications — Between database & application 70 35 What is Currently Happening in the Marketplace? org) — XML based (DTD) — Java Data Mining API spec request (JSR-000073) — Oracle, Sun, IBM, … — Support for data mining APIs on J2EE platforms — Build, manage, and score models programmatically — OLE DB for Data Mining — Microsoft — Table based — Incorporates PMML — It takes more than an XML standard to get two applications to work together and make users more productive 73 Data Mining Moving into the Database — Oracle 9i — Darwin team works for the DB group, not applications — Microsoft SQL Server — IBM Intelligent Miner V7R1 — NCR Teraminer — Benefits: — Minimize data movement — One stop shopping — Negatives: — Limited to analytics provided by vendor — Other applications might not be able to access mining functionality — Data transformations still an issue > ETL a major part of data management 74 37 SAS Enterprise Miner — Market Leader for analytical software — Large market share (70% of statistical software market) > 30,000 customers > 25 years of experience — GUI support for the SEMMA process — Workflow management — Full suite of data mining techniques 75 Enterprise Miner Capabilities Regression Models K Nearest Neighbor Neural Networks Decision Trees Self Organized Maps Text Mining Sampling Outlier Filtering Assessment 76 38 Enterprise Miner User Interface 77 SPSS Clementine 78 39 Insightful Miner 79 Oracle Darwin 80 40 Angoss KnowledgeSTUDIO 81 Usability and Understandability — Results of the data mining process are often difficult to understand — Graphically interact with data and results — Let user ask questions (poke and prod) — Let user move through the data — Reveal the data at several levels of detail, from a broad overview to the fine structure — Build trust in the results 82 41 User Needs to Trust the Results — Many models – which one is best?
Integration — Between applications — Between database & application 70 35 What is Currently Happening in the Marketplace? org) — XML based (DTD) — Java Data Mining API spec request (JSR-000073) — Oracle, Sun, IBM, … — Support for data mining APIs on J2EE platforms — Build, manage, and score models programmatically — OLE DB for Data Mining — Microsoft — Table based — Incorporates PMML — It takes more than an XML standard to get two applications to work together and make users more productive 73 Data Mining Moving into the Database — Oracle 9i — Darwin team works for the DB group, not applications — Microsoft SQL Server — IBM Intelligent Miner V7R1 — NCR Teraminer — Benefits: — Minimize data movement — One stop shopping — Negatives: — Limited to analytics provided by vendor — Other applications might not be able to access mining functionality — Data transformations still an issue > ETL a major part of data management 74 37 SAS Enterprise Miner — Market Leader for analytical software — Large market share (70% of statistical software market) > 30,000 customers > 25 years of experience — GUI support for the SEMMA process — Workflow management — Full suite of data mining techniques 75 Enterprise Miner Capabilities Regression Models K Nearest Neighbor Neural Networks Decision Trees Self Organized Maps Text Mining Sampling Outlier Filtering Assessment 76 38 Enterprise Miner User Interface 77 SPSS Clementine 78 39 Insightful Miner 79 Oracle Darwin 80 40 Angoss KnowledgeSTUDIO 81 Usability and Understandability — Results of the data mining process are often difficult to understand — Graphically interact with data and results — Let user ask questions (poke and prod) — Let user move through the data — Reveal the data at several levels of detail, from a broad overview to the fine structure — Build trust in the results 82 41 User Needs to Trust the Results — Many models – which one is best?