This article is weird. It makes an odd point, it includes the words "decision trees" seventeen times , and doesn't have much content. It feels like SEO bait.
Plus some flame bait, to attract links like this thread.
Why decision trees is the best data mining algorithm
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Re: Why decision trees is the best data mining algorithm
#12Decision trees are useful for the points enumerated in the blog article. One disadvantage of decision trees is that they can be slow on large data sets (> 1M examples). They are a batch algorithm, which means that you have look at all examples to build a tree, although they can be trained in an mini-online setting (only look at 10K examples per tree) which is faster. More importantly, decision tree induction involves…
They're also easy to overfit, similarly, finding representative training data is often non-trivial.
Re: Why decision trees is the best data mining algorithm
#13In this article there's a small screen shot of an application that looks like a decision tree designer ... does anyone know what this is? And is it public domain software?
I don't know what they're using, but if you want to play with decision trees I can highly recommend Weka, which is open-source.
Re: Why decision trees is the best data mining algorithm
#14Decision trees suffer from high variance. A slightly different sample might give you entirely different splits; using decision trees for data interpretation or feature selection is an art at best (and for some data sets uselessly unreliable).
>Decision trees are weak learners.
This is untrue. They're only used as weak learners in boosting because the tree depth is limited to some small constant.
>Decision trees run fast even with lots of observations and variables
I don't know all the decision tree learning algorithms, but at least some of the common ones run in O(features * samples * splits). That's not terrible, but you can handle much larger data sets optimizing w/ stochastic gradient descent or coordinate descent.
>Decision trees can easily handle unbalanced datasets.
This links to a post about bagging, which is not really specific to decision trees (but can be done with any learning algorithm)
Re: Why decision trees is the best data mining algorithm
#15In this article there's a small screen shot of an application that looks like a decision tree designer ... does anyone know what this is? And is it public domain software?