
Pros/Cons of Machine Learning Algorithms - ghosthamlet
https://coggle.it/diagram/WHeBqDIrJRk-kDDY/t/categories-of-algorithms-non-exhaustive
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chasedehan
I wouldn't pay attention to these groupings. They are artificially grouping on
arbitrary factors and paying attention to the pros/cons could lead you astray.

For example: Regression shouldn't be it's own group because regression is
commonly used in many decision tree algorithms. This group would be more apt
to be described as 'linear models'. There are many different types of
dimensionality reduction algorithms that are very different from LDA or PCA.
The ensemble group are mostly decision tree algorithms and while technically
they are ensembles, that is not what is thought of by most DS. AND, the NN
categories show some of the elements of an algorithm (back-prop for example)
as being an _actual_ algorithm. I could go on...

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ganeshkrishnan
I don't think linear regression should be in decision tree. Maybe logistic
regression.

The grouping on a high level is good and I kind of like it to send it to my
business team for them to make sense of the whole ml situation. Just my 2
cents.

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abhgh
"Regression" shouldn't be a separate category of algorithms given that the
other categories are learning algorithms like ANNs, SVMs etc which are also
used for regression. Also, it mentions Bayesian algorithms are fast - that's
not true except for some specific ones.

