86 search results - page 6 / 18 » Bagging, Boosting, and C4.5 |
ML
2000
ACM
13 years 7 months ago
2000
ACM
Bagging and boosting reduce error by changing both the inputs and outputs to form perturbed training sets, grow predictors on these perturbed training sets and combine them. A que...
DAGM
2011
Springer
12 years 7 months ago
2011
Springer
For face recognition from video streams often cues such as transcripts, subtitles or on-screen text are available. This information could be very valuable for improving the recogni...
MCS
2002
Springer
13 years 7 months ago
2002
Springer
Bagging and boosting are two popular ensemble methods that achieve better accuracy than a single classifier. These techniques have limitations on massive datasets, as the size of t...
ECML
2004
Springer
14 years 1 months ago
2004
Springer
In this paper we present a boosting approach to multiple instance learning. As weak hypotheses we use balls (with respect to various metrics) centered at instances of positive bags...
JMLR
2010
13 years 2 months ago
2010
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collecti...