Spring 2011 Seminar Series

DATE: February 24th
LOCATION: E62-550
TIME: 4:15pm
Reception immediately following in the same room

SPEAKER:
Carla E. Brodley

TITLE
Challenges in the Practical Application of Machine Learning

ABSTRACT
In this talk I will discuss the factors that impact the successful application of supervised machine learning. Driven by several interdisciplinary collaborations, we are addressing the problem of what to do when your your initial accuracy is lower than is acceptable to your domain experts. Low accuracy can be due to three factors: noise in the class labels, insufficient training data, and whether the features describing each training example are able to discriminate the classes. In this talk, I will discuss research efforts at Tufts addressing the second two factors. The first project re-examines active learning in the face of class imbalance and having access to multiple labelers with different levels of expertise. The second project examines how one might assess that the class distinctions are not supported by the features and how constraint-based clustering can be used to uncover the true class structure of the data. These two issues and their solutions will be explored in the context of two applications. The first is to create a global map of the land cover of the Earth's surface from remotely sensed data (satellite data). The second is to build a classifier for the semi-automated screening of biomedical citations for systematic reviews.