---
title: "Semi-Supervised Learning with Explicit Misclassification Modeling"
authors:
  - "Massih-Reza Amini"
  - "Patrick Gallinari"
doi: ""
url: "https://ijcai.org/proceedings/2003/82"
pdf: "https://ijcai.org/proceedings/2003/0082.pdf"
venue: "Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence"
year: 2003
pages: "555-559"
track: ""
keywords:
---

# Semi-Supervised Learning with Explicit Misclassification Modeling

Massih-Reza Amini, Patrick Gallinari

*Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence*, pages 555-559.

## Abstract

This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This algorithm optimizes the classification maximum likelihood of a set of labeledunlabeled data, using a variant form of the Classification Expectation Maximization (CEM) algorithm. Its originality is that it makes use of both unlabeled data and of a probabilistic misclassification model for these data. The parameters of the labelerror model are learned together with the classifier parameters. We demonstrate the effectiveness of the approach on four data-sets and show the advantages of this method over a previously developed semi-supervised algorithm which does not consider imperfections in the labeling process.