Talk:Decision tree

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Please help improve this article or section by expanding it. Further information might be found on the talk page or at requests for expansion. (April 2007)

Contents 1 Mention where to aquire the software used to generate the images in this wikipedia article 2 Disadvantages to decision trees 3 RE: Nothing said about decision trees ... Suggested Fix 4 Note 5 Nothing said about decision trees as a decision aid 6 Machine Learning 7 Addition 8 Example Confusing

[edit] Mention where to aquire the software used to generate the images in this wikipedia article

Woud like to learn more about the software, especially if open source web based or client binaries exist. —Preceding unsigned comment added by 130.207.180.93 (talk) 21:00, 12 December 2007 (UTC)

[edit] Disadvantages to decision trees

This article talks about the advantages to using decision trees but shouldn't it also include disadvantages too? User:noneforall October 14, 2007

[edit] RE: Nothing said about decision trees ... Suggested Fix

I think the note below is right on -- I'm amazed this entry hasn't been fixed.

My thought on a fix is that most of the decision tree entry needs to be moved to a more specific category ---- maybe decision tree learning. The data mining form of decision tree learning could be linked from a corrected decision tree page, within a parenthetical note about the confusion over terminology. Influence diagrams and decision analysis need to be referenced. Etc. I agree...there's do definition of what the diagrams mean--their spacing, colors, numbers, etc. I'm going to add a template and flag this article. Maybe it will get fixed then. RCanine 14:21, 6 April 2007 (UTC)

[edit] Note

Someone should probably point out the Z criterion (sqrt(positive weight * negative weight)), which is used by AdaBoost (Schapire and Singer). Earlier, it was analyzed by Kearns + Mansour (IIRC) in the case where example weights are uniform, and they cited Quinlan as first proposing it.

"...is a white box model" - Ahahahaha! The hilarity of the mental processes which lead anyone to think up the concept of a "white box" has brightened my day.

[edit] Nothing said about decision trees as a decision aid

I'm shocked that there is no mention of decision trees as a decision aid - where the expected values of various choices are calculated. This is what I understand as a Decision Tree - the stuff about their use in data mining is only of secondary importance to my mind.

For example a factory manager has to decide to invest in product A or product B (she cannot do both due to budget constrants). Product A is estimated to require two million pounds (or dollars if you like) of R&D investment, but only has a 50% chance of the research being successful and a product being obtained. It will then have a 30% chance of making a $5M profit, a 40% chance of making a $10M profit, and a 30% chance of not selling at all and making a loss of £1M for the manuafacturing costs. Product B on the other hand will cost $3M in R&D but has an 80% chance of making a $4M profit and a 20% chance of a $2M loss. If the company has a policy of maximising expected values, which should she go for?

This is just an example off the top of my head, but a more domestic example is of someone deciding to rent or buy their own house, along with a capital gain or loss depending on where house prices go and what the cost of renovation (or "fixing up" I think in AmEng) will be.

Decision trees are taught to teenage business students in the UK, but none of them would recognise this article. Decision trees are an example of an operations research or management science method.

The most important part of the article has been left out!

I'd also like to add that the highly mathematical formal description of decision trees is not going to be understood by most readers. Articles like this need to start with a very simple example that everyone can understand. --62.253.44.188 15:08, 6 August 2006 (UTC)

[edit] Machine Learning

Decision trees are also important in machine learning, not just management science. It would be good to see this distinction elaborated on in the article. There also needs to be more elaboration (or links to other articles) on constructing decision trees - mentioning ID3 and C4.5 is a start. Also, what about the example provided? How is the threshold value of 70 chosen for humidity? This seems wrong.

[edit] Addition

I tried to add a decision tree software to the list as it was in keeping with other links, why would informavores not qualify for entry on this page? —The preceding unsigned comment was added by Louharris (talk • contribs) 09:29, 3 April 2007 (UTC).

[edit] Example Confusing

I've done a few decision trees and I think the example given is confusing, especially without clarification on which colors mean what. I think perhaps a simpler example would be nice to start in order to illustrate the principle. fsiler 19:36, 30 July 2007 (UTC)