PhD Seminar Course on
Cagliari, September, 11-18, 2009
|Instructor:||Prof. Ludmila Kuncheva
Bangor University, Bangor Gwynedd, UK
|Venue:||Mocci Classroom, A Building|
Classifier ensembles are a growing area of pattern
recognition and machine learning. This course will set up the pattern
recognition background and will introduce the basics of classifier
ensembles. Ensemble approaches and methods will be presented including
the "classics" such as bagging, boosting, random subspace, random
forest end ECOC ensembles, as well as more recent additions to the
ensemble collection, e.g., rotation forest and random oracle ensembles.
We will take a look at the ensemble design strategies and combination
rules, and will discuss intuition and theory about why classifier
ensembles work. Diversity among the classifiers in the ensemble will be
explained, along with its relationship with the ensemble accuracy.
Cluster ensembles will be briefly presented, and we will touch upon
classifier ensembles for changing environments.
|Organizer:||Prof. Giorgio Giacinto
Dep. of Electrical and Electronic Engineering
University of Cagliari, Italy