In the typical nonparametric approach to classification in instance-based learning and data mining, random data (the training set of patterns) are collected and used to design a d...
Binay K. Bhattacharya, Kaustav Mukherjee, Godfried...
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
Background: Determination of the subcellular location of a protein is essential to understanding its biochemical function. This information can provide insight into the function o...
Josefine Sprenger, J. Lynn Fink, Rohan D. Teasdale
In this paper, we extend the recently proposed Core Vector Machine algorithm to the regression setting by generalizing the underlying minimum enclosing ball problem. The resultant...
In many important text classification problems, acquiring class labels for training documents is costly, while gathering large quantities of unlabeled data is cheap. This paper sh...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...