Talk:Boosting (machine learning)

message: The first sentence of the article defines boosting as a method for reducing bias. Isn't this incorrect? If boosting provides generalization, and variance refers to the variance of the model for different training sets (i.e. high variance means overfitting), then boosting should reduce variance and thereby increase bias. I'm confused about this, could someone please comment?
--EmanueleLM (talk) 07:43, 1 June 2016 (UTC)
thread_title:  Bias vs. Variance 

message: The explanation of strong vs. week learner is a bit confusing. Unfortunately, I am not the right person to explain it better.  —Preceding unsigned comment added by 193.171.142.61 (talk) 08:42, 7 December 2010 (UTC)
thread_title:  Strong vs. Weak 

message: Boosting is also a method for increasing the yield of a fisson bomb (Boosted fission weapon). Is that something that should be linked from this article? Or maybe put on the disambig. page for boost? --81.233.75.23 12:53, 1 June 2006 (UTC)
thread_title:  Boosting 

message: I removed this article from the computer vision category.  Boosting is probably used by some people to solve CV problems but
# It is not a methodology developed within CV or specific to CV
# Boosting is already listed under the ensemble learning category which is linked to the CV category via maching learning.
--KYN 22:36, 27 July 2007 (UTC)
thread_title:  Computer vision category 

message: I removed two articles from the references section.  Perhaps another references section should be started to include some of the additional research on boosting.
-- AaronArvey  —Preceding unsigned comment added by AaronArvey (talk • contribs) 01:15, 3 September 2007 (UTC)
thread_title:  Recent Articles 

message: The paper cited in reference to "convex potential boosters [not being able to] withstand random classification noise" states that "branching program based boosters" can withstand noise.
It would be really swell if someone knowledgeable could explain what "branching program based boosters" are. (Sorry that I can't)  —Preceding unsigned comment added by 194.103.189.41 (talk) 14:14, 23 March 2011 (UTC)
thread_title:  "branching program based boosters" 

message: I think that this article :
http://en.wikipedia.org/wiki/Boosting_methods_for_object_categorization
should be merge with this one. Anyone agree ?  — Preceding unsigned comment added by 207.139.190.179 (talk) 20:21, 4 December 2012 (UTC)
replies: text: Yes (even if rather belatedly). Klbrain (talk) 14:23, 26 July 2016 (UTC)
thread_title:  Merging article 

message: Boosting for multi-class categorization states at the second paragraph that The main flow of the algorithm is similar to the binary case. Perhaps the author intended the word flaw? Anyway there is no mention in the binary case of its main flow or flaw. So this needs to be clarified and possibly rewritten.--Gciriani (talk) 01:57, 3 June 2017 (UTC)
thread_title:  Boosting for multi-class categorization 

message: first sentence is:
"Boosting is a machine learning ensemble meta-algorithm for primarily reducing bias, and also variance[1]"
and that citation leads to:
https://web.archive.org/web/20150119081741/http://oz.berkeley.edu/~breiman/arcall96.pdf
I can't find anything in that paper that suggests boosting is "primarily for reducing bias". In fact it seems to be the opposite:
"Although both bagging and arcing[=boosting] reduce bias a bit, their major contribution to accuracy is in the large reduction of variance.  Arcing does better than bagging because it does better at variance reduction."
31.220.221.120 (talk) 14:04, 14 December 2017 (UTC)
thread_title:  first sentence is contradicted by its own citation