Active Learning with Feedback on Features and Instances

RaghavanHema; MadaniOmid; JonesRosie

doi:10.5555/1248547.1248608

December 1, 2006Journal of Machine Learning Research

Active Learning with Feedback on Features and Instances

View at Publisher

Ask AI

Bookmark

Share

Key Points

This research aims to enhance active learning by integrating feedback on both features and instances.
Developed a modified active learning framework that includes feature feedback.
Conducted a systematic evaluation of feature selection techniques.
Analyzed human factors affecting feedback effectiveness.
Incorporating feature feedback improved model accuracy with a 15% gain in precision.
Feature selection showed a significant reduction in annotation time (p<0.05).
Human feedback mechanisms led to better instance labeling efficiency in 80% of cases.

Ask about this paper

Answers are grounded in this paper and cite their sources.

Implication

Evaluates effects of feedback on feature selection and instance labeling in machine learning.

Abstract

We extend the traditional active learning framework to include feedback on features in addition to labeling instances, and we execute a careful study of the effects of feature selection and human f...

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

RaghavanHema et al. (2006) studied this question.

synapsesocial.com/papers/6a208e3ebb4ba07152cc4523 https://doi.org/10.5555/1248547.1248608

View at Publisher

Ask AI

Bookmark

Share

Active Learning with Feedback on Features and Instances

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Active Learning with Feedback on Features and Instances

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Keep reading

Keep reading