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muijonathan.com | ||
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www.johnmyleswhite.com
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| | | | | Introduction In my last post, I described how we can derive modes, medians and means as three natural solutions to the problem of summarizing a list of numbers, \((x_1, x_2, \ldots, x_n)\), using a single number, \(s\). In particular, we measured the quality of different potential summaries in three different ways, which led us to modes, medians and means respectively. Each of these quantities emerged from measuring the typical discrepancy between an element of the list, \(x_i\), and the summary, \(s\), ... | |
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www.jeremykun.com
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| | | Machine learning is broadly split into two camps, statistical learning and non-statistical learning. The latter we've started to get a good picture of on this blog; we approached Perceptrons, decision trees, and neural networks from a non-statistical perspective. And generally "statistical" learning is just that, a perspective. Data is phrased in terms of independent and dependent variables, and statistical techniques are leveraged against the data. In this post we'll focus on the simplest example of thi... | ||
