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Top data mining algorithms in plain English
- ma2rten 11y agoI feel like some of these algorithms are outdated, i.e. rarely used anymore: C4.5, Apriori, CART. Instead I would suggest: Logistic Regression, RandomForest and Neural Networks.
- shazeline 11y agoCART forms the basis of the decision trees used by scikit-learn's implementation of random forests [1]. CART may be old, but definitely not outdated. [1] https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/tree/tree.py#L542 https://github.com/scikit-learn/scikit-learn/blob/master/skl...
- leeleelee 11y agoVery, very awesome article.
- stellographer 11y agoI 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.
- blumkvist 11y agoSo you want to do math without knowing how to do math?
- stellographer 11y agoI'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 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 http://en.wikipedia.org/wiki/Firefly_algorithm
- profinger 11y agoThis is what I was thinking as well! The explanation is good but it's the actual steps of the algorithm that are the difficult part!
- zatkin 11y agoWow, this is an awesome read. I especially like how each algorithm starts with a simple explanation and then dives deeper into each lesser known vocabulary.
- kiril-me 11y agoYou can significantly improve C4.5 speed using See5/C5.0
- lessthunk 11y agoGreat to get specialist knowledge/understanding into the mainstream.
- tomelders 11y agoI'll add my noise to the cacophony and agree that this is a grat article. I've been struggling with an idea for a while, and this has opened up a whole new horizon of possibility for me. So thanks.
- aaronsnoswell 11y agoWhat an excellent article!
- Grue3 11y agoHow convenient, I'm currently tasked with classifying some data and this will surely come in handy.
- mrfusion 11y agoI'd be interested to see some computer vision algorithms explained this way too, SIFT, SURF?
- zild3d 11y agoI'd be interested in just about every algorithm explained this way! And as a side note some of these algorithms certainly are used in computer vision, k-means for example in clustering/segmentation. https://courses.cs.washington.edu/courses/cse576/12sp/notes/remote.pdf https://courses.cs.washington.edu/courses/cse576/12sp/notes/...
- honodk 11y agoHave a look at this: https://gilscvblog.wordpress.com/2013/08/18/a-short-introduction-to-descriptors/#more-3 https://gilscvblog.wordpress.com/2013/08/18/a-short-introduc... . I found it very helpful!
- aerovistae 11y agoCan 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.
- bipin_nag 11y agoI 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.
- natch 11y agoAwesome. What is a 'kernel' btw?
- diego_moita 11y agoWow! It explains, in 20-30 minutes, what took me a whole semester to study at the University. I only wish it had a little about Neural Networks and Deep Learning.
- deleted 11y ago[deleted]