A client has inquired about producing a decision tree from data which could include:
- ID of brand purchased - Importance ratings (1-10 scale) for a number of relevant attributes (price, strength, recommended by a friend, etc.) In other words, a rating of how important each attribute is in the decision as to which brand to purchase. I've just run a test decision tree using the closest thing to a similar data set, that I have at hand . But only one attribute was selected for plotting. I used the "Tree" package for this test. Question: - Does one usually get good decision trees using data of this kind? Thanks very much in advance to all for any info. -- View this message in context: http://r.789695.n4.nabble.com/Good-Decision-Trees-with-Product-Purchased-Data-tp4632438.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
