Analytics

Machine Learning and You: K-Means Clustering

We are seeing a tremendous amount of interest in people wanting to learn more about machine learning, AI, data mining, and predictive analytics. Our presentations addressing these topics are often some of the best attended

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The Four Realms of Analytics

The four realms of analytics: descriptive analytics, predictive analytics, prescriptive analytics, and diagnostic analytics can be organized along a dimension from rules-based to probability-based and the dimension of time (past and future). This simple two-by-two matrix offers a powerful framework for organizing and describing the differences between analytical processes. While the four realms are often cited, they seldom appear without there being considerable confusion in understanding the distinctions between them. Rather than relying on dictionary definitions and unspecified connotations, this simple framework is offered as a way to communicate different types of analytics to lay audiences.

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Oracle Data Mining vs. SAS is like Support Vector Machines vs. Neural Nets

I’m part of a small group of mathematics enthusiasts in Kansas City who meet about once a month on Saturday mornings to drink coffee and discuss mathematics. This past weekend it was my turn to do a presentation to the rest of the group and I chose to speak on the mathematical foundations of the Support Vector Machine algorithm in Oracle Data Mining. While I wasn’t surprised that some in the group had a better handle on Vapnik-Chervonenkis theory than I and gently “guided” me a few times, I was somewhat surprised at their positive reaction to my characterization of the “Oracle” approach to data mining in contrast with the “SAS” approach.
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