The model-free, data-driven technique discussed here is so basic that it can easily be implemented in Excel, and we actually provide an Excel implementation. It is surprising that this technique does not pre-date standard linear regression, and is rarely if ever used by statisticians and data scientists. It is related to kriging and nearest neighbor interpolation, and apparently first mentioned in 1965 by Harvard scientists working on GIS (geographic information systems). It was referred…

While the Bernoulli and binomial distributions are among the first ones taught in any elementary statistical course, the Poisson-Binomial is rarely mentioned. It is however one of the simplest discrete distributions, with applications in survey analysis, see here. In this article, we are dealing with…

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After more than 10 years being involved with Data Science Central, initially as the founder, and most recently being acquired by TechTarget, I have decided to pursue new interests. TechTarget now has a great team taking care of DSC, and I will still be involved as a consultant to make sure that everything continues to run smoothly and that the quality standards are maintained and even enhanced. In my new role, I will…

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Originally posted by Michael Grogan. 

In this tutorial, we are going to use the K-Nearest Neighbors (KNN) algorithm to solve a classification problem. Firstly, what exactly do we mean by classification?

Classification across a variable means that results are categorised into a particular group. e.g. classifying a fruit as either an apple or an orange.

The KNN algorithm is one the most basic, yet most commonly used…

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