XLMiner 3.2

XLMiner has a set of features based on statistical and machine learning methods
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XLMiner provides a comprehensive set of analysis features based both on statistical and machine learning methods. A problem or a data set can be analyzed by several methods. It is usually a good idea to try different approaches, compare their results, and then choose a model that suits the problem well.

Limits

XLMiner can work with large data sets which may exceed the limits in Excel. A standard procedure is to sample data from a larger database, bring it into Excel to fit a model, and, in the case of supervised learning routines, score output back out to the database. In the standard edition of XLMiner, this feature is supported for Oracle, SQL Server and Access databases. This feature is not available in the education or free web trial versions. The free web trial demo version handles a maximum of 200 records per partition

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