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Top data mining algorithms in plain English

rayli.net

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Re: Top data mining algorithms in plain English

#21

Post by stellographer »

blumkvist wrote: post #10
stellographer wrote: post #3

I found this article useful. What I was really hoping for was a layman's translation of the maths on wikipedia [ie. how to implement]. But this is a good jumping off point for figuring out which black box to use.

So you want to do math without knowing how to do math?

I'm just saying it takes about 30 seconds to explain the Metropolis-Hastings algorithm in plain english, and the wikipedia article is almost intentionally esoteric on the matter:

http://en.wikipedia.org/wiki/Metropolis–Hastings_algorithm

Meanwhile the much more complex Firefly algorithm is adequately explained in just 3 sentences that are obvious to understand:

http://en.wikipedia.org/wiki/Firefly_algorithm

Re: Top data mining algorithms in plain English

#22

Post by bipin_nag »

aerovistae wrote: post #13

Can we have more things like this, please? This is an AMAZING introduction to these concepts. I wish more people on Hacker News would make such clear blog posts for their personal share of cryptic knowledge, helping other people through the door.

I also want that, the side-by-side comparison specially. The follow up discussions are also helpful, someone mentioned about C5.0 I didn't know about. There are lot of algorithms/steps pieces that are needed when solving the machine learning puzzle. The article was very helpful.

Re: Top data mining algorithms in plain English

#23

Post by natch »

Bostonian wrote: post #17
natch wrote: post #15

Awesome. What is a 'kernel' btw?

In kernel density estimation, each observed data point is spread out by a "kernel" function such as a Gaussian, essentially exp(-0.5*x^2), or uniform function, f(x) = 1 for |x| < 0.5. So I think of a "kernel" as a function used to distribute a point mass.

In English?
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