- XLMiner 2018
介紹XLMiner™ is a comprehensive data mining add-in for Excel. Data mining is a discovery-driven data analysis technology used for identifying patterns and relationships in data sets. With overwhelming amounts of data now available from transaction systems and external data sources, organizations are presented with increasing opportunities to understand their data and gain insights into it. Data mining is still an emerging field, and is a convergence of fields like statistics, machine learning, and artificial intelligence.
Version 2018 Now Available for Excel 2007 / 2010 / 2013 / 2016
- Powerful data exploration and visualization features, in additional to its data preparation, data mining, and time series forecasting methods.
- Support for Microsoft's PowerPivot add-in, which handles 'Big Data' and integrates multiple, disparate data sources into one in-memory database inside Excel.
- Support for Excel 2016, and the new PowerPivot add-in that ships with the new Excel.
XLMiner® for Windows is the only comprehensive data mining add-in for Excel, with neural nets, classification and regression trees, logistic regression, linear regression, Bayes classifier, K-nearest neighbors, discriminant analysis, association rules, clustering, principal components.XLMiner Version 3 is now available, with new time series analysis, plus the ability to save models for later review, plus the ability to score saved models to new data.
XLMiner comes in 4 editions. All require Windows (XP, Vista, or Windows 7) and Excel 2000, 2003, 2007 and 2010.
• Demo edition (functional 30-day web download)
• Education edition
• Professional edition
• Academic Research edition
The Academic Research edition is virtually the same as the Professional edition, except that purchasers must be on the faculty of a college or university. To learn about the capabilities of the different versions, click here.
Online course in data mining
Statistics.com offers online courses in data mining featuring, some of which illustrate the use of XLMiner. Click here for more information
Suggested text: From Wiley Books, Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner, features XLMiner and provides both a theoretical and practical understanding of the key methods of classification, prediction, reduction and exploration that are at the heart of data mining. In addition, it presents a business decision-making context for these methods and uses real business cases and data to illustrate the application and interpretation of these methods.
Data Pre-processing with Talend Open Studio
An important, and time consuming part of data mining is the work required to get data into proper shape to permit data mining algorithms to work. Talend Open Sutdio is an open source program that helps with this-click here to read more and here to download.
Are you interested in data mining, but lacking access to costly data mining tools?
Looking for a package that's comprehensive yet affordable?
XLMiner offers a full repertoire of techniques for classification, prediction, affinity analysis, data exploration, and data reduction. It is in use at
• Northrup Grumman • Monsanto
• National Institutes of Health • ExxonMobil
• Westing house (Savannah River) • US Army
• JD Powers • FDA
• NASA • Experion
• Bell Atlantic • National Inst. of Standards & Technology
• Pitney Bowes • Fidelity Investments
• Centers for Disease Control • Blackstone Group
The educational version (used at at MIT's Sloan School, Bowling Green State Univ., Duke's Fuqua School, Georgetown's McDonough School, Indiana Univ., UCLA's Anderson School and elsewhere), is highly affordable - as little as $49 per student. XLMiner combines Cytel's accurate and reliable algorithms (implemented as DLL's) with Excel's familiar interface and workspace, and includes facilities for sampling from and scoring to large databases. Works with Excel 2000 and later.
Read a comparative review of XLMiner (along with SAS Enterprise Miner, SPSS Clementine, GhostMiner and Quadstone) in The American Statistician, November 2003. "...easy-to-use...an excellent, inexpensive add-on that greatly expands the capabilities of Excel."
• Partitioning into training, validation, and test datasets
• Multiple linear regression with subset selection
• Logistic regression with subset selection
• Discriminant analysis
• Naive Bayes classification
• Classification and regression trees
• k-Nearest neighbors
• Neural networks
• Association rules
• Principal components
• k-Means clustering
• Hierarchical clustering
• Time series
• Save models for later review
• Score saved models (separate XLMcalc module)
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