Ensemble Multi-label Feature Selection Using Weighted Harmonic Mean

S. S. Mohanrasu; R. Rakkiyappan

doi:10.1007/978-981-97-3180-0_44

ScienceGate Book Chapters

BOOK-CHAPTER

Ensemble Multi-label Feature Selection Using Weighted Harmonic Mean

S. S. Mohanrasu R. Rakkiyappan

Year: 2024 Lecture notes in networks and systems Pages: 661-673 Publisher: Springer International Publishing

DOI: 10.1007/978-981-97-3180-0_44

Get Full-Text PDF Get Analytical Report

Keywords:

Harmonic mean Feature selection Pattern recognition (psychology) Mathematics Artificial intelligence Selection (genetic algorithm) Feature (linguistics) Computer science Statistics Philosophy

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.25

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Image Retrieval and Classification Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Algorithms and Data Compression

Physical Sciences → Computer Science → Artificial Intelligence

Ensemble Multi-label Feature Selection Using Weighted Harmonic Mean

Metrics

Topics

Related Documents

Feature selection for multi-label text data: An ensemble approach using geometric mean aggregation

MLIFT: Enhancing Multi-label Classifier with Ensemble Feature Selection

A Feature Selection Method Using Weighted Clusterer Ensemble

Multi-label classification with weighted classifier selection and stacked ensemble

Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection