
Machine Learning Cheat Sheet Map - cognibits
http://scikit-learn.org/stable/tutorial/machine_learning_map/index.html
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dj-wonk
Just a note. scikit has logistic regression, but it isn't shown at the top
level. It is contained within `LinearSVC` on the diagram: [http://scikit-
learn.org/stable/modules/generated/sklearn.lin...](http://scikit-
learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html#sklearn.linear_model.LogisticRegression)

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ColinWright
It's currently down - is it the same one discussed at some length a year ago?

[https://news.ycombinator.com/item?id=5831512](https://news.ycombinator.com/item?id=5831512)

Here are some other resources for machine learning, not necessarily restricted
to the algorithms implemented in SciKit:

[http://eferm.com/wp-content/uploads/2011/05/cheat3.pdf](http://eferm.com/wp-
content/uploads/2011/05/cheat3.pdf)

[http://peekaboo-vision.blogspot.ca/2013/01/machine-
learning-...](http://peekaboo-vision.blogspot.ca/2013/01/machine-learning-
cheat-sheet-for-scikit.html)

[http://rise.cse.iitm.ac.in/wiki/index.php/Introduction_to_Ma...](http://rise.cse.iitm.ac.in/wiki/index.php/Introduction_to_Machine_Learning)

[http://mlg.eng.cam.ac.uk/creed/Notes/ML_Compendium.pdf](http://mlg.eng.cam.ac.uk/creed/Notes/ML_Compendium.pdf)

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Pamar
"Mathbabe" is currently working on something similar:
[http://mathbabe.org/2014/08/28/a-decision-tree-for-
decision-...](http://mathbabe.org/2014/08/28/a-decision-tree-for-decision-
trees/) even if she has just started working on this (and she mentions the OP
item herself).

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dj-wonk
Dimensionality reduction can be a goal in and of itself, but many of the same
techniques (i.e. feature selection) are useful precursors for classification,
clustering, and regression. It would be nice to capture that on the diagram.
More arrows, please. :)

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dj-wonk
The "text data" decision point seems arbitrary and in my opinion, not useful.
I've analyzed text data with a Naive Bayes a classifier as well as SVM. I
really like what the chart is trying to be, but I think it is editorializing
too much.

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cognibits
I guess the chart is designed to those who are doing their first steps in the
machine learning world. It makes order. BTW I have nothing to do with scikit-
learn, I shared it as I found it to be useful.

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dj-wonk
Thanks for sharing it. I think it is a good start; it gives people something
to react and build upon.

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dj-wonk
I don't see why the diagram has SVC and ensemble classifiers located in the
"not working" path from KNeighbors Classifiers. It is reasonable to use an
ensemble method independent of whether nearest neighbors works.

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lazycrazyowl
This looks very similar to the map described on dlib C++ Machine Learning
library page. [http://dlib.net/ml_guide.svg](http://dlib.net/ml_guide.svg)

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dj-wonk
I'd suggest giving Random Forests a call-out instead of leaving them hidden
under ensemble methods in the diagram. I realize this is a clarity / detail
tradeoff.

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iLoch
"This project has been temporarily blocked for exceeding its bandwidth
threshold" I wonder why no one uses SourceForge anymore..

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CyberShadow
What's going on here? The page is hosted on the scikit-learn.org domain, and I
don't see any redirects or frames pointing to SourceForge. Or is SourceForge
allowing projects to point arbitrary domains at it?

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ogrisel
Yes it's hosted on SF with a CNAME dns entry. We want to move to github but we
need to update the website build infra to do so.

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a8da6b0c91d
dlib did something similar with different results.

[http://dlib.net/ml_guide.svg](http://dlib.net/ml_guide.svg)

