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oslandia.com | ||
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janakiev.com
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| | | | | There are many ways to compare countries and cities and many measurements to choose from. We can see how they perform economically, or how their demographics differ, but what if we take a look at data available in OpenStreetMap? In this article, we explore just that with the help of a procedure called t-SNE. | |
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www.oranlooney.com
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| | | | | In the previous article in this series we distinguished between two kinds of unsupervised learning (cluster analysis and dimensionality reduction) and discussed the former in some detail. In this installment we turn our attention to the later. In dimensionality reduction we seek a function \(f : \mathbb{R}^n \mapsto \mathbb{R}^m\) where \(n\) is the dimension of the original data \(\mathbf{X}\) and \(m\) is less than or equal to \(n\). That is, we want to map some high dimensional space into some lower dimensional space. | |
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smyachenkov.com
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| | | | | K-Means is a very common and powerful clusterization algorithm widely used in an unsupervised machine learning tasks for dividing data into categories. The only decision you have to make is the number of clusters you want your data to be divided into - k number. Sometimes you already know how many categories you need to have. It depends a lot on the type of your problem, your data, and the problems you are solving. | |
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wattsupwiththat.com
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| | | Reposted from the Fabius Maximus blog By Larry Kummer, Editor / 17 November 2019 Summary: Let's hit "pause" in the climate wars and see how we got here, where we are going, and what we can learn from this mess. "I can't use this result. It doesn't support the narrative." Photo 99364552 © Standret -... | ||
