Work

MICCLLR: A Generalized Multiple-Instance Learning Algorithm Using Class Conditional Log Likelihood Ratio

Year: 2007

Type: article

Abstract: We propose a new generalized multiple-instance learn-ing (MIL) algorithm, MICCLLR (multiple-instance class conditional likelihood ratio), that converts the MI data into a single meta-instance data allowing any propositional classifier to be applied. Experimental results on a wide range of MI data sets show that MICCLLR is competitive with some of the best performing MIL algorithms reported in literature. 1.

Source: Iowa State University Digital Repository (Iowa State University)

Authors: Yasser EL‐Manzalawy, Vasant Honavar

Institution: Iowa State University

Language: English

Topic: Machine Learning and Algorithms

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W1498013111

FWCI: 0.276

Cites: 22

Cited by: 1

Related to: 10