H
Huan Liu
Researcher at Arizona State University
Publications - 1284
Citations - 69383
Huan Liu is an academic researcher from Arizona State University. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 110, co-authored 727 publications receiving 57903 citations. Previous affiliations of Huan Liu include Aims Community College & National University of Singapore.
Papers
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Journal ArticleDOI
Feature Selection for Classification
Manoranjan Dash,Huan Liu +1 more
TL;DR: This survey identifies the future research areas in feature selection, introduces newcomers to this field, and paves the way for practitioners who search for suitable methods for solving domain-specific real-world applications.
Journal ArticleDOI
Toward integrating feature selection algorithms for classification and clustering
TL;DR: With the categorizing framework, the efforts toward-building an integrated system for intelligent feature selection are continued, and an illustrative example is presented to show how existing feature selection algorithms can be integrated into a meta algorithm that can take advantage of individual algorithms.
Proceedings Article
Feature selection for high-dimensional data: a fast correlation-based filter solution
TL;DR: A novel concept, predominant correlation, is introduced, and a fast filter method is proposed which can identify relevant features as well as redundancy among relevant features without pairwise correlation analysis.
Journal Article
Efficient Feature Selection via Analysis of Relevance and Redundancy
TL;DR: It is shown that feature relevance alone is insufficient for efficient feature selection of high-dimensional data, and a new framework is introduced that decouples relevance analysis and redundancy analysis.
Journal ArticleDOI
Fake News Detection on Social Media: A Data Mining Perspective
TL;DR: Wang et al. as discussed by the authors presented a comprehensive review of detecting fake news on social media, including fake news characterizations on psychology and social theories, existing algorithms from a data mining perspective, evaluation metrics and representative datasets.