Our airline case study, originally done in Excel, shows how XLMiner users can build predictive models from Big Data that match the accuracy of a similar HortonWorks case study using a public FAA airline dataset, but without any of the complexity of Hadoop, Pig, Python and other developer tools.
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It's all point-and-click, and if you've used XLMiner in Excel, you already know how to use. Then you can bring in data from Excel workbooks, CSV files, SQL databases, or our Apache Spark Big Data cluster, explore and transform your data, use a wide range of machine learning methods to build a model with predictive power for your data, and evaluate and compare different models. To use, you simply visit the site and register to create an account. It offers business analysts point-and-click tools to create predictive analytics models themselves, without being expert data scientists or programmers. XLMiner for the Webĭevelopers working in C++, C#, Java, Python or R can jump down to our discussion of XLMiner SDK, but let's start with a tool that anyone can use: is a new SaaS (software as a service) platform for data mining, text mining, forecasting, and predictive analytics using only a browser.
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The XLMiner® brand now covers predictive analytics in desktop Excel with XLMiner Pro and Platform, in Excel Online and Google Sheets with XLMiner Analysis ToolPak, on the Web for everyone with, and embedded in applications with XLMiner SDK.
Frontline's predictive analytics tools just took two "quantum leaps": We've introduced XLMiner SDK, a new, powerful toolkit for software developers who want to use data mining and text mining in their own applications, and we've introduced, "predictive analytics software as a service" with point-and-click ease.
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