Books on the topic 'Feature selection'

Liu, Huan, and Hiroshi Motoda, eds. Feature Extraction, Construction and Selection. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5725-8.

Cakmakov, Dusan. Feature selection for pattern recognition. Skopje: Informa, 2002.

Saunders, Craig, Marko Grobelnik, Steve Gunn, and John Shawe-Taylor, eds. Subspace, Latent Structure and Feature Selection. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11752790.

Bolón-Canedo, Verónica, Noelia Sánchez-Maroño, and Amparo Alonso-Betanzos. Feature Selection for High-Dimensional Data. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21858-8.

Wan, Cen. Hierarchical Feature Selection for Knowledge Discovery. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-97919-9.

1958-, Liu Huan, ed. Spectral feature selection for data mining. Boca Raton, FL: CRC Press, 2012.

Stańczyk, Urszula, and Lakhmi C. Jain, eds. Feature Selection for Data and Pattern Recognition. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-45620-0.

Bolón-Canedo, Verónica, and Amparo Alonso-Betanzos. Recent Advances in Ensembles for Feature Selection. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-90080-3.

Lu, Rui. Feature Selection for High Dimensional Causal Inference. [New York, N.Y.?]: [publisher not identified], 2020.

Liu, Huan, and Hiroshi Motoda. Feature Selection for Knowledge Discovery and Data Mining. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5689-3.

Liu, Huan. Feature Selection for Knowledge Discovery and Data Mining. Boston, MA: Springer US, 1998.

Nilsson, Roland. Statistical feature selection: With applications in life science. Linko ping: Department of Physcis, Chemistry and Biology, Linko ping University, 2007.

Liu, Huan. Feature selection for knowledge discovery and data mining. Boston: Kluwer Academic, 1998.

Huan, Liu. Feature selection for knowledge discovery and data mining. Boston: Kluwer Academic Publishers, 1998.

Stańczyk, Urszula, Beata Zielosko, and Lakhmi C. Jain, eds. Advances in Feature Selection for Data and Pattern Recognition. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-67588-6.

Jensen, Richard. Computational intelligence and feature selection: Rough and fuzzy approaches. Oxford: Wiley, 2008.

1958-, Liu Huan, and Motoda Hiroshi, eds. Feature extraction, construction and selection: A data mining perspective. Boston: Kluwer Academic, 1998.

Liu, Huan. Feature Extraction, Construction and Selection: A Data Mining Perspective. Boston, MA: Springer US, 1998.

K, Kokula Krishna Hari, and K. Saravanan, eds. Exploratory Analysis of Feature Selection Techniques in Medical Image Processing. Tiruppur, Tamil Nadu, India: Association of Scientists, Developers and Faculties, 2016.

Abualigah, Laith Mohammad Qasim. Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-10674-4.

Hinders, Mark K. Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49395-0.

Okun, Oleg. Feature selection and ensemble methods for bioinformatics: Algorithmic classification and implementations. Hershey PA: Medical Information Science Reference, 2011.

Raza, Muhammad Summair, and Usman Qamar. Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4965-1.

Raza, Muhammad Summair, and Usman Qamar. Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9166-9.

Hristea, Florentina T. The Naïve Bayes Model for Unsupervised Word Sense Disambiguation: Aspects Concerning Feature Selection. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

Geological Survey (U.S.) and Geological Survey (U.S.)., eds. Production of a national 1:1,000,000-scale hydrography dataset for the United States: Feature selection, simplification, and refinement. Reston, Va: U.S. Dept. of the Interior, U.S. Geological Survey, 2009.

SLSFS 2005 (2005 Bohinj, Slovenia). Subspace, latent structure and feature selection: Statistical and Optimization Perspectives Workshop, SLSFS 2005, Bohinj, Slovenia, February 23-25, 2005 : revised selected papers. Berlin: Springer, 2006.

Haldenby, Michael R. D. An investigation of the characterisations of schools and schooling in a selection of feature films made in Britain and the United States of America since 1939. [Coventry]: typescript, 1988.

Bondarenko, Natal'ya. Pattern recognition. The initial course of theory. ru: INFRA-M Academic Publishing LLC., 2024. http://dx.doi.org/10.12737/2111834.

B, Holt Rodger, Rogers V. C. 1941-, and National Risk Management Research Laboratory (U.S.), eds. Residential Radon Resistant Construction Features Selection System: Final Report. Washington, DC: U.S. Environmental Protection Agency, Office of Research and Development, 1996.

Kuhn, Max, and Kjell Johnson. Feature Engineering and Selection. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9781315108230.

Kuhn, Max, and Kjell Johnson. Feature Engineering and Selection. Taylor & Francis Group, 2021.

Computational methods of feature selection. Boca Raton: Chapman & Hall/CRC, 2008.

Liu, Huan, and Hiroshi Motoda. Computational Methods of Feature Selection. Taylor & Francis Group, 2007.

Liu, Huan, and Hiroshi Motoda. Computational Methods of Feature Selection. Taylor & Francis Group, 2007.

Liu, Huan, and Hiroshi Motoda. Computational Methods of Feature Selection. Taylor & Francis Group, 2007.

Liu, Huan, and Zheng Alan Zhao. Spectral Feature Selection for Data Mining. Taylor & Francis Group, 2011.

Liu, Huan, and Zheng Alan Zhao. Spectral Feature Selection for Data Mining. Taylor & Francis Group, 2011.

Liu, Huan, and Zheng Alan Zhao. Spectral Feature Selection for Data Mining. Taylor & Francis Group, 2011.

Alonso-Betanzos, Amparo, Noelia Sánchez-Maroño, and Verónica Bolón-Canedo. Feature Selection for High-Dimensional Data. Springer, 2015.

Zhao, Zheng. Spectral Feature Selection for Data Mining. Taylor & Francis Group, 2012.

Alonso-Betanzos, Amparo, Noelia Sánchez-Maroño, and Verónica Bolón-Canedo. Feature Selection for High-Dimensional Data. Springer, 2016.

Liu, Huan, and Zheng Alan Zhao. Spectral Feature Selection for Data Mining. Taylor & Francis Group, 2011.

Liu, Huan, and Zheng Alan Zhao. Spectral Feature Selection for Data Mining. Taylor & Francis Group, 2018.

Alonso-Betanzos, Amparo, Noelia Sánchez-Maroño, and Verónica Bolón-Canedo. Feature Selection for High-Dimensional Data. Springer, 2015.

Spectral Feature Selection for Data Mining. Chapman and Hall/CRC, 2011.

Feature Selection in Machine Learning with Python. Lulu Press, Inc., 2022.

Feature Selection for Predicting Pilot Mental Workload. Storming Media, 2000.

Stańczyk, Urszula, and Lakhmi C. Jain. Feature Selection for Data and Pattern Recognition. Springer Berlin / Heidelberg, 2016.

Alonso-Betanzos, Amparo, and Verónica Bolón-Canedo. Recent Advances in Ensembles for Feature Selection. Springer International Publishing AG, 2019.