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You searched for subject:(Subset selection). Showing records 1 – 30 of 33 total matches.

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Université Catholique de Louvain

1. Tits, Cédric. Application of feature subset selection on meaningful features leads to promising results for spike sorting.

Degree: 2016, Université Catholique de Louvain

Understanding the visual system is a real interest since it contributes to one of the most important sense for human: the vision. To achieve this… (more)

Subjects/Keywords: Feature Subset Selection; Spike Sorting

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Tits, C. (2016). Application of feature subset selection on meaningful features leads to promising results for spike sorting. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/thesis:4588

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Tits, Cédric. “Application of feature subset selection on meaningful features leads to promising results for spike sorting.” 2016. Thesis, Université Catholique de Louvain. Accessed April 21, 2019. http://hdl.handle.net/2078.1/thesis:4588.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Tits, Cédric. “Application of feature subset selection on meaningful features leads to promising results for spike sorting.” 2016. Web. 21 Apr 2019.

Vancouver:

Tits C. Application of feature subset selection on meaningful features leads to promising results for spike sorting. [Internet] [Thesis]. Université Catholique de Louvain; 2016. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2078.1/thesis:4588.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tits C. Application of feature subset selection on meaningful features leads to promising results for spike sorting. [Thesis]. Université Catholique de Louvain; 2016. Available from: http://hdl.handle.net/2078.1/thesis:4588

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Sydney

2. Yu, Baosheng. Robust Diversity-Driven Subset Selection in Combinatorial Optimization .

Degree: 2019, University of Sydney

Subset selection is fundamental in combinatorial optimization with applications in biology, operations research, and computer science, especially machine learning and computer vision. However, subset selection(more)

Subjects/Keywords: subset selection; bandits; submodular optimization

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APA (6th Edition):

Yu, B. (2019). Robust Diversity-Driven Subset Selection in Combinatorial Optimization . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/19834

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Yu, Baosheng. “Robust Diversity-Driven Subset Selection in Combinatorial Optimization .” 2019. Thesis, University of Sydney. Accessed April 21, 2019. http://hdl.handle.net/2123/19834.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Yu, Baosheng. “Robust Diversity-Driven Subset Selection in Combinatorial Optimization .” 2019. Web. 21 Apr 2019.

Vancouver:

Yu B. Robust Diversity-Driven Subset Selection in Combinatorial Optimization . [Internet] [Thesis]. University of Sydney; 2019. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2123/19834.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yu B. Robust Diversity-Driven Subset Selection in Combinatorial Optimization . [Thesis]. University of Sydney; 2019. Available from: http://hdl.handle.net/2123/19834

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Urbana-Champaign

3. Kwon, Hee Youn. New developments in causal inference using balance optimization subset selection.

Degree: PhD, Systems & Entrepreneurial Engr, 2018, University of Illinois – Urbana-Champaign

 Causal inference with observational data has drawn attention across various fields. These observational studies typically use matching methods which find matched pairs with similar covariate… (more)

Subjects/Keywords: Causal Analysis; Optimization; Subset Selection

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APA (6th Edition):

Kwon, H. Y. (2018). New developments in causal inference using balance optimization subset selection. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/100968

Chicago Manual of Style (16th Edition):

Kwon, Hee Youn. “New developments in causal inference using balance optimization subset selection.” 2018. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed April 21, 2019. http://hdl.handle.net/2142/100968.

MLA Handbook (7th Edition):

Kwon, Hee Youn. “New developments in causal inference using balance optimization subset selection.” 2018. Web. 21 Apr 2019.

Vancouver:

Kwon HY. New developments in causal inference using balance optimization subset selection. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2018. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2142/100968.

Council of Science Editors:

Kwon HY. New developments in causal inference using balance optimization subset selection. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2018. Available from: http://hdl.handle.net/2142/100968


University of Illinois – Urbana-Champaign

4. Dutta, Shouvik. Applications of balance optimization subset selection.

Degree: MS, Industrial Engineering, 2016, University of Illinois – Urbana-Champaign

 Balance Optimization Subset Selection (BOSS) is a framework designed to be used for causal inference on observational data. The theoretical foundation for the BOSS framework… (more)

Subjects/Keywords: Subset Selection; Netflix; Basketball; Recommendations

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APA (6th Edition):

Dutta, S. (2016). Applications of balance optimization subset selection. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/92872

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Dutta, Shouvik. “Applications of balance optimization subset selection.” 2016. Thesis, University of Illinois – Urbana-Champaign. Accessed April 21, 2019. http://hdl.handle.net/2142/92872.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Dutta, Shouvik. “Applications of balance optimization subset selection.” 2016. Web. 21 Apr 2019.

Vancouver:

Dutta S. Applications of balance optimization subset selection. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2142/92872.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Dutta S. Applications of balance optimization subset selection. [Thesis]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/92872

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Rochester

5. Mahalanabis, Satyaki. Subset and sample selection for graphical models: Gaussian processes, Ising models and Gaussian mixture models.

Degree: PhD, 2012, University of Rochester

 Probabilistic Graphical Models are a popular method of representing complex joint distributions in which stochastic dependence between subsets of random variables is expressed in terms… (more)

Subjects/Keywords: Graphical models; Sample selection; Subset selection

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mahalanabis, S. (2012). Subset and sample selection for graphical models: Gaussian processes, Ising models and Gaussian mixture models. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/25118

Chicago Manual of Style (16th Edition):

Mahalanabis, Satyaki. “Subset and sample selection for graphical models: Gaussian processes, Ising models and Gaussian mixture models.” 2012. Doctoral Dissertation, University of Rochester. Accessed April 21, 2019. http://hdl.handle.net/1802/25118.

MLA Handbook (7th Edition):

Mahalanabis, Satyaki. “Subset and sample selection for graphical models: Gaussian processes, Ising models and Gaussian mixture models.” 2012. Web. 21 Apr 2019.

Vancouver:

Mahalanabis S. Subset and sample selection for graphical models: Gaussian processes, Ising models and Gaussian mixture models. [Internet] [Doctoral dissertation]. University of Rochester; 2012. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/1802/25118.

Council of Science Editors:

Mahalanabis S. Subset and sample selection for graphical models: Gaussian processes, Ising models and Gaussian mixture models. [Doctoral Dissertation]. University of Rochester; 2012. Available from: http://hdl.handle.net/1802/25118


University of Rochester

6. Pearson, Alexander T. Subset Selection for High-Dimensional Data, with Applications to Gene Array Data.

Degree: PhD, 2009, University of Rochester

 Identifying those genes that are differentially expressed in individuals with cancer could lead to new avenues of treatment or prevention. Gene array information can be… (more)

Subjects/Keywords: Subset Selection; Gene Array; High Dimensional Data

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APA (6th Edition):

Pearson, A. T. (2009). Subset Selection for High-Dimensional Data, with Applications to Gene Array Data. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/8411

Chicago Manual of Style (16th Edition):

Pearson, Alexander T. “Subset Selection for High-Dimensional Data, with Applications to Gene Array Data.” 2009. Doctoral Dissertation, University of Rochester. Accessed April 21, 2019. http://hdl.handle.net/1802/8411.

MLA Handbook (7th Edition):

Pearson, Alexander T. “Subset Selection for High-Dimensional Data, with Applications to Gene Array Data.” 2009. Web. 21 Apr 2019.

Vancouver:

Pearson AT. Subset Selection for High-Dimensional Data, with Applications to Gene Array Data. [Internet] [Doctoral dissertation]. University of Rochester; 2009. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/1802/8411.

Council of Science Editors:

Pearson AT. Subset Selection for High-Dimensional Data, with Applications to Gene Array Data. [Doctoral Dissertation]. University of Rochester; 2009. Available from: http://hdl.handle.net/1802/8411


Georgia Tech

7. Lin, Chen-ju. New Methods for Eliminating Inferior Treatments in Clinical Trials.

Degree: PhD, Industrial and Systems Engineering, 2007, Georgia Tech

 Multiple comparisons and selection procedures are commonly studied in research and employed in application. Clinical trial is one of popular fields to which the subject(more)

Subjects/Keywords: Subset selection; Multiple comparisons

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APA (6th Edition):

Lin, C. (2007). New Methods for Eliminating Inferior Treatments in Clinical Trials. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/16262

Chicago Manual of Style (16th Edition):

Lin, Chen-ju. “New Methods for Eliminating Inferior Treatments in Clinical Trials.” 2007. Doctoral Dissertation, Georgia Tech. Accessed April 21, 2019. http://hdl.handle.net/1853/16262.

MLA Handbook (7th Edition):

Lin, Chen-ju. “New Methods for Eliminating Inferior Treatments in Clinical Trials.” 2007. Web. 21 Apr 2019.

Vancouver:

Lin C. New Methods for Eliminating Inferior Treatments in Clinical Trials. [Internet] [Doctoral dissertation]. Georgia Tech; 2007. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/1853/16262.

Council of Science Editors:

Lin C. New Methods for Eliminating Inferior Treatments in Clinical Trials. [Doctoral Dissertation]. Georgia Tech; 2007. Available from: http://hdl.handle.net/1853/16262

8. KONG EFANG. On semi-parametric model and subset selection.

Degree: 2006, National University of Singapore

Subjects/Keywords: subset selection; single-index models

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APA (6th Edition):

EFANG, K. (2006). On semi-parametric model and subset selection. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/15611 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/2/bitstream

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

EFANG, KONG. “On semi-parametric model and subset selection.” 2006. Thesis, National University of Singapore. Accessed April 21, 2019. http://scholarbank.nus.edu.sg/handle/10635/15611 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/2/bitstream.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

EFANG, KONG. “On semi-parametric model and subset selection.” 2006. Web. 21 Apr 2019.

Vancouver:

EFANG K. On semi-parametric model and subset selection. [Internet] [Thesis]. National University of Singapore; 2006. [cited 2019 Apr 21]. Available from: http://scholarbank.nus.edu.sg/handle/10635/15611 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/2/bitstream.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

EFANG K. On semi-parametric model and subset selection. [Thesis]. National University of Singapore; 2006. Available from: http://scholarbank.nus.edu.sg/handle/10635/15611 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/2/bitstream

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


North Carolina State University

9. Alston, April Valdessa. Heart Rate Regulation: Modeling and Analysis.

Degree: PhD, Applied Mathematics, 2009, North Carolina State University

 Orthostatic stress tests, such as postural change from sitting to standing and head-up tilt, are common noninvasive procedures used to study short-term regulation of the… (more)

Subjects/Keywords: mathematical modeling; heart rate regulation; sensitivity analysis; subset selection

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APA (6th Edition):

Alston, A. V. (2009). Heart Rate Regulation: Modeling and Analysis. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/4108

Chicago Manual of Style (16th Edition):

Alston, April Valdessa. “Heart Rate Regulation: Modeling and Analysis.” 2009. Doctoral Dissertation, North Carolina State University. Accessed April 21, 2019. http://www.lib.ncsu.edu/resolver/1840.16/4108.

MLA Handbook (7th Edition):

Alston, April Valdessa. “Heart Rate Regulation: Modeling and Analysis.” 2009. Web. 21 Apr 2019.

Vancouver:

Alston AV. Heart Rate Regulation: Modeling and Analysis. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2019 Apr 21]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4108.

Council of Science Editors:

Alston AV. Heart Rate Regulation: Modeling and Analysis. [Doctoral Dissertation]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4108


North Carolina State University

10. Wu, Yujun. Controlling Variable Selection By the Addition of Pseudo-Variables.

Degree: PhD, Statistics, 2004, North Carolina State University

 Many variable selection procedures have been developed in the literature for linear regression models. We propose a new and general approach, the False Selection Rate… (more)

Subjects/Keywords: forward selection; false selection rate; subset selection; variable selection

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APA (6th Edition):

Wu, Y. (2004). Controlling Variable Selection By the Addition of Pseudo-Variables. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/5883

Chicago Manual of Style (16th Edition):

Wu, Yujun. “Controlling Variable Selection By the Addition of Pseudo-Variables.” 2004. Doctoral Dissertation, North Carolina State University. Accessed April 21, 2019. http://www.lib.ncsu.edu/resolver/1840.16/5883.

MLA Handbook (7th Edition):

Wu, Yujun. “Controlling Variable Selection By the Addition of Pseudo-Variables.” 2004. Web. 21 Apr 2019.

Vancouver:

Wu Y. Controlling Variable Selection By the Addition of Pseudo-Variables. [Internet] [Doctoral dissertation]. North Carolina State University; 2004. [cited 2019 Apr 21]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/5883.

Council of Science Editors:

Wu Y. Controlling Variable Selection By the Addition of Pseudo-Variables. [Doctoral Dissertation]. North Carolina State University; 2004. Available from: http://www.lib.ncsu.edu/resolver/1840.16/5883


University of California – Riverside

11. Bappy, Md Jawadul Hasan. Context-Aware Informative Sample Selection and Image Forgery Detection.

Degree: Electrical Engineering, 2018, University of California – Riverside

 Most of the computer vision methods assume that data will be labeled and availablebeforehand in order to train a good recognition model. However, it becomes… (more)

Subjects/Keywords: Artificial intelligence; Active Learning; Anomaly Detection; Deep Network; LSTM; Subset Selection; Typicality

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APA (6th Edition):

Bappy, M. J. H. (2018). Context-Aware Informative Sample Selection and Image Forgery Detection. (Thesis). University of California – Riverside. Retrieved from http://www.escholarship.org/uc/item/21k56036

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Bappy, Md Jawadul Hasan. “Context-Aware Informative Sample Selection and Image Forgery Detection.” 2018. Thesis, University of California – Riverside. Accessed April 21, 2019. http://www.escholarship.org/uc/item/21k56036.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Bappy, Md Jawadul Hasan. “Context-Aware Informative Sample Selection and Image Forgery Detection.” 2018. Web. 21 Apr 2019.

Vancouver:

Bappy MJH. Context-Aware Informative Sample Selection and Image Forgery Detection. [Internet] [Thesis]. University of California – Riverside; 2018. [cited 2019 Apr 21]. Available from: http://www.escholarship.org/uc/item/21k56036.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bappy MJH. Context-Aware Informative Sample Selection and Image Forgery Detection. [Thesis]. University of California – Riverside; 2018. Available from: http://www.escholarship.org/uc/item/21k56036

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Queens University

12. Eghtesadi, Zahra. A Mean-Squared-Error-Based Methodology for Parameter Ranking and Selection to Obtain Accurate Model Predictions at Key Operating Conditions .

Degree: Chemical Engineering, 2015, Queens University

 In this thesis, a new mean-squared-error (MSE)-based criterion, rCCW, is proposed to select the optimal number of parameters to estimate from the ranked list of… (more)

Subjects/Keywords: Model selection criteria; Mean-squared error; Operating conditions; Parameter subset selection; Non-invertible Fisher information matrix

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APA (6th Edition):

Eghtesadi, Z. (2015). A Mean-Squared-Error-Based Methodology for Parameter Ranking and Selection to Obtain Accurate Model Predictions at Key Operating Conditions . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/12680

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Eghtesadi, Zahra. “A Mean-Squared-Error-Based Methodology for Parameter Ranking and Selection to Obtain Accurate Model Predictions at Key Operating Conditions .” 2015. Thesis, Queens University. Accessed April 21, 2019. http://hdl.handle.net/1974/12680.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Eghtesadi, Zahra. “A Mean-Squared-Error-Based Methodology for Parameter Ranking and Selection to Obtain Accurate Model Predictions at Key Operating Conditions .” 2015. Web. 21 Apr 2019.

Vancouver:

Eghtesadi Z. A Mean-Squared-Error-Based Methodology for Parameter Ranking and Selection to Obtain Accurate Model Predictions at Key Operating Conditions . [Internet] [Thesis]. Queens University; 2015. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/1974/12680.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Eghtesadi Z. A Mean-Squared-Error-Based Methodology for Parameter Ranking and Selection to Obtain Accurate Model Predictions at Key Operating Conditions . [Thesis]. Queens University; 2015. Available from: http://hdl.handle.net/1974/12680

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Urbana-Champaign

13. Nikoukar, Romina. Near-optimal inversion of incoherent scatter radar measurements: coding schemes, processing techniques, and experiments.

Degree: PhD, 1200, 2010, University of Illinois – Urbana-Champaign

 Accurate and efficient estimation of the key ionospheric state parameters such as electron density, ion composition, and electron and ion temperatures is required to understand… (more)

Subjects/Keywords: Incoherent scatter radar; Inversion; Parameter estimation; Deconvolution methods; Regularization; Amplitude modulation; Model order selection; subset selection

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APA (6th Edition):

Nikoukar, R. (2010). Near-optimal inversion of incoherent scatter radar measurements: coding schemes, processing techniques, and experiments. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/16990

Chicago Manual of Style (16th Edition):

Nikoukar, Romina. “Near-optimal inversion of incoherent scatter radar measurements: coding schemes, processing techniques, and experiments.” 2010. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed April 21, 2019. http://hdl.handle.net/2142/16990.

MLA Handbook (7th Edition):

Nikoukar, Romina. “Near-optimal inversion of incoherent scatter radar measurements: coding schemes, processing techniques, and experiments.” 2010. Web. 21 Apr 2019.

Vancouver:

Nikoukar R. Near-optimal inversion of incoherent scatter radar measurements: coding schemes, processing techniques, and experiments. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2010. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2142/16990.

Council of Science Editors:

Nikoukar R. Near-optimal inversion of incoherent scatter radar measurements: coding schemes, processing techniques, and experiments. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2010. Available from: http://hdl.handle.net/2142/16990


Universidade de Brasília

14. Susanne Tainá Romalho Maciel. Fatoração QR como ferramenta para a determinação de poços principais em redes de monitoramento de aqüíferos freáticos.

Degree: 2008, Universidade de Brasília

Monitoring networks of piezometric motion are increasingly used for evaluation and management of aquifers. A pivoted version of the QR factorization was used in four… (more)

Subjects/Keywords: GEOCIENCIAS; seleção de subconjuntos; monitoramento de água subterrânea; QR factorization; Fatoração QR; subset selection; groundwater monitoring

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APA (6th Edition):

Maciel, S. T. R. (2008). Fatoração QR como ferramenta para a determinação de poços principais em redes de monitoramento de aqüíferos freáticos. (Thesis). Universidade de Brasília. Retrieved from http://bdtd.bce.unb.br/tedesimplificado/tde_busca/arquivo.php?codArquivo=4570

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Maciel, Susanne Tainá Romalho. “Fatoração QR como ferramenta para a determinação de poços principais em redes de monitoramento de aqüíferos freáticos.” 2008. Thesis, Universidade de Brasília. Accessed April 21, 2019. http://bdtd.bce.unb.br/tedesimplificado/tde_busca/arquivo.php?codArquivo=4570.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Maciel, Susanne Tainá Romalho. “Fatoração QR como ferramenta para a determinação de poços principais em redes de monitoramento de aqüíferos freáticos.” 2008. Web. 21 Apr 2019.

Vancouver:

Maciel STR. Fatoração QR como ferramenta para a determinação de poços principais em redes de monitoramento de aqüíferos freáticos. [Internet] [Thesis]. Universidade de Brasília; 2008. [cited 2019 Apr 21]. Available from: http://bdtd.bce.unb.br/tedesimplificado/tde_busca/arquivo.php?codArquivo=4570.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Maciel STR. Fatoração QR como ferramenta para a determinação de poços principais em redes de monitoramento de aqüíferos freáticos. [Thesis]. Universidade de Brasília; 2008. Available from: http://bdtd.bce.unb.br/tedesimplificado/tde_busca/arquivo.php?codArquivo=4570

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Texas – Austin

15. -3269-6167. Graph analytics and subset selection problems in machine learning.

Degree: Electrical and Computer Engineering, 2018, University of Texas – Austin

 In this dissertation we examine two topics relevant to modern machine learning research: 1) Subgraph counting and 2) High-dimensional subset selection. The former can be… (more)

Subjects/Keywords: Machine learning; Approximation algorithms; Graph analytics; Graph algorithms; Subset selection; Submodular optimization; Weak submodularity; Restricted strong convexity; Streaming algorithms; Interpretability

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APA (6th Edition):

-3269-6167. (2018). Graph analytics and subset selection problems in machine learning. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68499

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

-3269-6167. “Graph analytics and subset selection problems in machine learning.” 2018. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/68499.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

-3269-6167. “Graph analytics and subset selection problems in machine learning.” 2018. Web. 21 Apr 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-3269-6167. Graph analytics and subset selection problems in machine learning. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/68499.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

-3269-6167. Graph analytics and subset selection problems in machine learning. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68499

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation


North Carolina State University

16. Pope, Scott R. Parameter Identification in Lumped Compartment Cardiorespiratory Models.

Degree: PhD, Applied Mathematics, 2009, North Carolina State University

 The parameter identification problem attempts to find parameter values that cause the solution of a predictive model to match data. In this work, parameters in… (more)

Subjects/Keywords: lumped compartment models; parameter estimation; subset selection; non-linear least squares optimization; cardiovascular models; respiratory models

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APA (6th Edition):

Pope, S. R. (2009). Parameter Identification in Lumped Compartment Cardiorespiratory Models. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/4600

Chicago Manual of Style (16th Edition):

Pope, Scott R. “Parameter Identification in Lumped Compartment Cardiorespiratory Models.” 2009. Doctoral Dissertation, North Carolina State University. Accessed April 21, 2019. http://www.lib.ncsu.edu/resolver/1840.16/4600.

MLA Handbook (7th Edition):

Pope, Scott R. “Parameter Identification in Lumped Compartment Cardiorespiratory Models.” 2009. Web. 21 Apr 2019.

Vancouver:

Pope SR. Parameter Identification in Lumped Compartment Cardiorespiratory Models. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2019 Apr 21]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4600.

Council of Science Editors:

Pope SR. Parameter Identification in Lumped Compartment Cardiorespiratory Models. [Doctoral Dissertation]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4600


University of Iowa

17. Zhang, Tao. Discrepancy-based algorithms for best-subset model selection.

Degree: PhD, Biostatistics, 2013, University of Iowa

  The selection of a best-subset regression model from a candidate family is a common problem that arises in many analyses. In best-subset model selection,… (more)

Subjects/Keywords: Best-subset model selection; Gauss discrepancy; Generalized linear models; Kullback-Leibler discrepancy; Linear models; Multistage procedure; Biostatistics

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APA (6th Edition):

Zhang, T. (2013). Discrepancy-based algorithms for best-subset model selection. (Doctoral Dissertation). University of Iowa. Retrieved from https://ir.uiowa.edu/etd/4800

Chicago Manual of Style (16th Edition):

Zhang, Tao. “Discrepancy-based algorithms for best-subset model selection.” 2013. Doctoral Dissertation, University of Iowa. Accessed April 21, 2019. https://ir.uiowa.edu/etd/4800.

MLA Handbook (7th Edition):

Zhang, Tao. “Discrepancy-based algorithms for best-subset model selection.” 2013. Web. 21 Apr 2019.

Vancouver:

Zhang T. Discrepancy-based algorithms for best-subset model selection. [Internet] [Doctoral dissertation]. University of Iowa; 2013. [cited 2019 Apr 21]. Available from: https://ir.uiowa.edu/etd/4800.

Council of Science Editors:

Zhang T. Discrepancy-based algorithms for best-subset model selection. [Doctoral Dissertation]. University of Iowa; 2013. Available from: https://ir.uiowa.edu/etd/4800


Université Catholique de Louvain

18. Chang, Chia-Tche. Heuristic optimization methods for three matrix problems.

Degree: 2012, Université Catholique de Louvain

Optimization is a major field in applied mathematics. Many applications involve the search of the best solution to a problem according to some criterion. Depending… (more)

Subjects/Keywords: Heuristics; Metaheuristics; Feature selection; Dynamical system; Switching system; Genetic algorithm; Optimization; Algorithmics; Oriented bounding box; Subset selection; Joint spectral radius; Computational methods; Experimental analysis; Computational geometry

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APA (6th Edition):

Chang, C. (2012). Heuristic optimization methods for three matrix problems. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/120115

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chang, Chia-Tche. “Heuristic optimization methods for three matrix problems.” 2012. Thesis, Université Catholique de Louvain. Accessed April 21, 2019. http://hdl.handle.net/2078.1/120115.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chang, Chia-Tche. “Heuristic optimization methods for three matrix problems.” 2012. Web. 21 Apr 2019.

Vancouver:

Chang C. Heuristic optimization methods for three matrix problems. [Internet] [Thesis]. Université Catholique de Louvain; 2012. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2078.1/120115.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chang C. Heuristic optimization methods for three matrix problems. [Thesis]. Université Catholique de Louvain; 2012. Available from: http://hdl.handle.net/2078.1/120115

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Cincinnati

19. Dong, Ming. A New Measure of Classifiability and its Applications.

Degree: PhD, Engineering : Electrical Engineering, 2001, University of Cincinnati

 Characterizing the difficulty of a pattern classification problem is an open and challenging problem in machine learning. While some progress has been made in understanding… (more)

Subjects/Keywords: pattern recognition and classification; classifiability; Bayes Error; decision tree; feature subset selection

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APA (6th Edition):

Dong, M. (2001). A New Measure of Classifiability and its Applications. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1003516324

Chicago Manual of Style (16th Edition):

Dong, Ming. “A New Measure of Classifiability and its Applications.” 2001. Doctoral Dissertation, University of Cincinnati. Accessed April 21, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1003516324.

MLA Handbook (7th Edition):

Dong, Ming. “A New Measure of Classifiability and its Applications.” 2001. Web. 21 Apr 2019.

Vancouver:

Dong M. A New Measure of Classifiability and its Applications. [Internet] [Doctoral dissertation]. University of Cincinnati; 2001. [cited 2019 Apr 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1003516324.

Council of Science Editors:

Dong M. A New Measure of Classifiability and its Applications. [Doctoral Dissertation]. University of Cincinnati; 2001. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1003516324


Massey University

20. Beale, Ian R. Subset selection routing : modelling and heuristics.

Degree: PhD, Operations Research, 2002, Massey University

 This theoretically practical thesis relates to the field of subset selection routing problems, in which there are a set of customers available to be serviced… (more)

Subjects/Keywords: Transportation; Mathematical models; Operations research; Maximum collection problem; Decision-making; Subset selection routing

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APA (6th Edition):

Beale, I. R. (2002). Subset selection routing : modelling and heuristics. (Doctoral Dissertation). Massey University. Retrieved from http://hdl.handle.net/10179/1949

Chicago Manual of Style (16th Edition):

Beale, Ian R. “Subset selection routing : modelling and heuristics.” 2002. Doctoral Dissertation, Massey University. Accessed April 21, 2019. http://hdl.handle.net/10179/1949.

MLA Handbook (7th Edition):

Beale, Ian R. “Subset selection routing : modelling and heuristics.” 2002. Web. 21 Apr 2019.

Vancouver:

Beale IR. Subset selection routing : modelling and heuristics. [Internet] [Doctoral dissertation]. Massey University; 2002. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/10179/1949.

Council of Science Editors:

Beale IR. Subset selection routing : modelling and heuristics. [Doctoral Dissertation]. Massey University; 2002. Available from: http://hdl.handle.net/10179/1949

21. PRADEEP KUMAR ATREY. Information assimilation in Multimedia surveillance systems.

Degree: 2007, National University of Singapore

Subjects/Keywords: Information assimilation; Multimedia surveillance; Optimal media subset selection; Event detection

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APA (6th Edition):

ATREY, P. K. (2007). Information assimilation in Multimedia surveillance systems. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/23028 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/2/bitstream

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

ATREY, PRADEEP KUMAR. “Information assimilation in Multimedia surveillance systems.” 2007. Thesis, National University of Singapore. Accessed April 21, 2019. http://scholarbank.nus.edu.sg/handle/10635/23028 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/2/bitstream.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

ATREY, PRADEEP KUMAR. “Information assimilation in Multimedia surveillance systems.” 2007. Web. 21 Apr 2019.

Vancouver:

ATREY PK. Information assimilation in Multimedia surveillance systems. [Internet] [Thesis]. National University of Singapore; 2007. [cited 2019 Apr 21]. Available from: http://scholarbank.nus.edu.sg/handle/10635/23028 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/2/bitstream.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

ATREY PK. Information assimilation in Multimedia surveillance systems. [Thesis]. National University of Singapore; 2007. Available from: http://scholarbank.nus.edu.sg/handle/10635/23028 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/2/bitstream

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

22. LI JUXIN. Optimal computing budget allocation for multi-objective simulation optimization.

Degree: 2012, National University of Singapore

Subjects/Keywords: multi-objective; simulation optimization; subset selection; computing budget; Pareto-optimal

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APA (6th Edition):

JUXIN, L. (2012). Optimal computing budget allocation for multi-objective simulation optimization. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/38760 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/2/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/1/bitstream

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

JUXIN, LI. “Optimal computing budget allocation for multi-objective simulation optimization.” 2012. Thesis, National University of Singapore. Accessed April 21, 2019. http://scholarbank.nus.edu.sg/handle/10635/38760 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/2/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/1/bitstream.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

JUXIN, LI. “Optimal computing budget allocation for multi-objective simulation optimization.” 2012. Web. 21 Apr 2019.

Vancouver:

JUXIN L. Optimal computing budget allocation for multi-objective simulation optimization. [Internet] [Thesis]. National University of Singapore; 2012. [cited 2019 Apr 21]. Available from: http://scholarbank.nus.edu.sg/handle/10635/38760 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/2/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/1/bitstream.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

JUXIN L. Optimal computing budget allocation for multi-objective simulation optimization. [Thesis]. National University of Singapore; 2012. Available from: http://scholarbank.nus.edu.sg/handle/10635/38760 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/2/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/1/bitstream

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

23. Verwaeren, Jan. Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction.

Degree: 2014, Ghent University

Subjects/Keywords: Mathematics and Statistics; machine learning; unmixing; subset selection; mathematical optimization; compositional data

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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APA (6th Edition):

Verwaeren, J. (2014). Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction. (Thesis). Ghent University. Retrieved from http://hdl.handle.net/1854/LU-4418612

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Verwaeren, Jan. “Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction.” 2014. Thesis, Ghent University. Accessed April 21, 2019. http://hdl.handle.net/1854/LU-4418612.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Verwaeren, Jan. “Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction.” 2014. Web. 21 Apr 2019.

Vancouver:

Verwaeren J. Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction. [Internet] [Thesis]. Ghent University; 2014. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/1854/LU-4418612.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Verwaeren J. Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction. [Thesis]. Ghent University; 2014. Available from: http://hdl.handle.net/1854/LU-4418612

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


De Montfort University

24. Ali, Isse. Analysing and predicting differences between methylated and unmethylated DNA sequence features.

Degree: PhD, 2015, De Montfort University

 DNA methylation is involved in various biological phenomena, and its dysregulation has been demonstrated as being correlated with a number of human disease processes, including… (more)

Subjects/Keywords: 572.8; DNA methylation prediction; CpG islands; DNA feature/pattern; Methylation gender differences; feature subset selection; imbalanced data modelling; ageing and DNA methylation; cancer and DNA methylation

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APA (6th Edition):

Ali, I. (2015). Analysing and predicting differences between methylated and unmethylated DNA sequence features. (Doctoral Dissertation). De Montfort University. Retrieved from http://hdl.handle.net/2086/12616

Chicago Manual of Style (16th Edition):

Ali, Isse. “Analysing and predicting differences between methylated and unmethylated DNA sequence features.” 2015. Doctoral Dissertation, De Montfort University. Accessed April 21, 2019. http://hdl.handle.net/2086/12616.

MLA Handbook (7th Edition):

Ali, Isse. “Analysing and predicting differences between methylated and unmethylated DNA sequence features.” 2015. Web. 21 Apr 2019.

Vancouver:

Ali I. Analysing and predicting differences between methylated and unmethylated DNA sequence features. [Internet] [Doctoral dissertation]. De Montfort University; 2015. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2086/12616.

Council of Science Editors:

Ali I. Analysing and predicting differences between methylated and unmethylated DNA sequence features. [Doctoral Dissertation]. De Montfort University; 2015. Available from: http://hdl.handle.net/2086/12616


Texas A&M University

25. Tracy, James L. Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly.

Degree: PhD, Entomology, 2018, Texas A&M University

 Correlative ecological niche models (ENMs) are essential for investigating distributions of species and natural phenomena via environmental correlates across broad fields, including entomology and pyrogeography… (more)

Subjects/Keywords: Random Feature Selection; Feature Subset Ensemble; Species Distribution Model; Pyrogeography; Danaus plexippus; Migratory Niche Model; Kernel Density Estimation Migratory Model; Insect Roadkill Niche Model

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APA (6th Edition):

Tracy, J. L. (2018). Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174342

Chicago Manual of Style (16th Edition):

Tracy, James L. “Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly.” 2018. Doctoral Dissertation, Texas A&M University. Accessed April 21, 2019. http://hdl.handle.net/1969.1/174342.

MLA Handbook (7th Edition):

Tracy, James L. “Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly.” 2018. Web. 21 Apr 2019.

Vancouver:

Tracy JL. Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/1969.1/174342.

Council of Science Editors:

Tracy JL. Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/174342


Unitec New Zealand

26. Ho, Trung Minh. Evaluating spammer detection systems for Twitter.

Degree: 2017, Unitec New Zealand

 Twitter is a popular Social Network Service. It is a web application with dual roles of online social network and microblogging. Users use Twitter to… (more)

Subjects/Keywords: Twitter; spam detection; spam drift; optimisation subset of features; evaluation workbench; feature selection; machine learning; 080303 Computer System Security; 080109 Pattern Recognition and Data Mining

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APA (6th Edition):

Ho, T. M. (2017). Evaluating spammer detection systems for Twitter. (Thesis). Unitec New Zealand. Retrieved from http://hdl.handle.net/10652/4525

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ho, Trung Minh. “Evaluating spammer detection systems for Twitter.” 2017. Thesis, Unitec New Zealand. Accessed April 21, 2019. http://hdl.handle.net/10652/4525.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ho, Trung Minh. “Evaluating spammer detection systems for Twitter.” 2017. Web. 21 Apr 2019.

Vancouver:

Ho TM. Evaluating spammer detection systems for Twitter. [Internet] [Thesis]. Unitec New Zealand; 2017. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/10652/4525.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ho TM. Evaluating spammer detection systems for Twitter. [Thesis]. Unitec New Zealand; 2017. Available from: http://hdl.handle.net/10652/4525

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

27. Ferreira, Ednaldo José. "Abordagem genética para seleção de um conjunto reduzido de características para construção de ensembles de redes neurais: aplicação à língua eletrônica".

Degree: Mestrado, Ciências de Computação e Matemática Computacional, 2005, University of São Paulo

As características irrelevantes, presentes em bases de dados de diversos domínios, deterioram a acurácia de predição de classificadores induzidos por algoritmos de aprendizado de máquina.… (more)

Subjects/Keywords: algoritmo genético; ensemble; ensemble; feature subset selection; genetic algorithm; neural networks; redes neurais artificiais; seleção de características

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APA (6th Edition):

Ferreira, E. J. (2005). "Abordagem genética para seleção de um conjunto reduzido de características para construção de ensembles de redes neurais: aplicação à língua eletrônica". (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18052006-143603/ ;

Chicago Manual of Style (16th Edition):

Ferreira, Ednaldo José. “"Abordagem genética para seleção de um conjunto reduzido de características para construção de ensembles de redes neurais: aplicação à língua eletrônica".” 2005. Masters Thesis, University of São Paulo. Accessed April 21, 2019. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18052006-143603/ ;.

MLA Handbook (7th Edition):

Ferreira, Ednaldo José. “"Abordagem genética para seleção de um conjunto reduzido de características para construção de ensembles de redes neurais: aplicação à língua eletrônica".” 2005. Web. 21 Apr 2019.

Vancouver:

Ferreira EJ. "Abordagem genética para seleção de um conjunto reduzido de características para construção de ensembles de redes neurais: aplicação à língua eletrônica". [Internet] [Masters thesis]. University of São Paulo; 2005. [cited 2019 Apr 21]. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18052006-143603/ ;.

Council of Science Editors:

Ferreira EJ. "Abordagem genética para seleção de um conjunto reduzido de características para construção de ensembles de redes neurais: aplicação à língua eletrônica". [Masters Thesis]. University of São Paulo; 2005. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18052006-143603/ ;

28. Pila, Adriano Donizete. Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets.

Degree: Mestrado, Ciências de Computação e Matemática Computacional, 2001, University of São Paulo

No Aprendizado de Máquina Supervisionado – AM – o algoritmo de indução trabalha com um conjunto de exemplos de treinamento, no qual cada exemplo é constituído de… (more)

Subjects/Keywords: aprendizado de máquina; feature subset selection; machine learning; rough sets; seleção automática de atributos

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APA (6th Edition):

Pila, A. D. (2001). Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13022002-153921/ ;

Chicago Manual of Style (16th Edition):

Pila, Adriano Donizete. “Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets.” 2001. Masters Thesis, University of São Paulo. Accessed April 21, 2019. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13022002-153921/ ;.

MLA Handbook (7th Edition):

Pila, Adriano Donizete. “Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets.” 2001. Web. 21 Apr 2019.

Vancouver:

Pila AD. Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets. [Internet] [Masters thesis]. University of São Paulo; 2001. [cited 2019 Apr 21]. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13022002-153921/ ;.

Council of Science Editors:

Pila AD. Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets. [Masters Thesis]. University of São Paulo; 2001. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13022002-153921/ ;

29. Sigweni, Boyce B. An investigation of feature weighting algorithms and validation techniques using blind analysis for analogy-based estimation.

Degree: PhD, 2016, Brunel University

 Context: Software effort estimation is a very important component of the software development life cycle. It underpins activities such as planning, maintenance and bidding. Therefore,… (more)

Subjects/Keywords: 005.1; Feature subset selection; Software effort estimation; Case-based reasoning; Researcher bias; Cross-validation approaches

…3.1 The filter approach for feature subset selection . . . . . . . . . . . . . . . . . 43… …Thesis Chapter 1 still NP-hard, is feature subset selection where features are assigned… …less daunting approach, although still NP-hard, is feature subset selection where features… …are assigned weights of {0, 1}. Until recently feature subset selection has been… …feature weighting tend to outperform feature subset selection methods [153]. This is… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sigweni, B. B. (2016). An investigation of feature weighting algorithms and validation techniques using blind analysis for analogy-based estimation. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/12797 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.687658

Chicago Manual of Style (16th Edition):

Sigweni, Boyce B. “An investigation of feature weighting algorithms and validation techniques using blind analysis for analogy-based estimation.” 2016. Doctoral Dissertation, Brunel University. Accessed April 21, 2019. http://bura.brunel.ac.uk/handle/2438/12797 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.687658.

MLA Handbook (7th Edition):

Sigweni, Boyce B. “An investigation of feature weighting algorithms and validation techniques using blind analysis for analogy-based estimation.” 2016. Web. 21 Apr 2019.

Vancouver:

Sigweni BB. An investigation of feature weighting algorithms and validation techniques using blind analysis for analogy-based estimation. [Internet] [Doctoral dissertation]. Brunel University; 2016. [cited 2019 Apr 21]. Available from: http://bura.brunel.ac.uk/handle/2438/12797 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.687658.

Council of Science Editors:

Sigweni BB. An investigation of feature weighting algorithms and validation techniques using blind analysis for analogy-based estimation. [Doctoral Dissertation]. Brunel University; 2016. Available from: http://bura.brunel.ac.uk/handle/2438/12797 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.687658


University of Tennessee – Knoxville

30. Howe, John Andrew. A New Generation of Mixture-Model Cluster Analysis with Information Complexity and the Genetic EM Algorithm.

Degree: 2009, University of Tennessee – Knoxville

 In this dissertation, we extend several relatively new developments in statistical model selection and data mining in order to improve one of the workhorse statistical… (more)

Subjects/Keywords: mixture modeling; nonparametric estimation; subset selection; influence detection; evidence-based medical diagnostics; unsupervised classification; robust estimation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Howe, J. A. (2009). A New Generation of Mixture-Model Cluster Analysis with Information Complexity and the Genetic EM Algorithm. (Doctoral Dissertation). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_graddiss/863

Chicago Manual of Style (16th Edition):

Howe, John Andrew. “A New Generation of Mixture-Model Cluster Analysis with Information Complexity and the Genetic EM Algorithm.” 2009. Doctoral Dissertation, University of Tennessee – Knoxville. Accessed April 21, 2019. https://trace.tennessee.edu/utk_graddiss/863.

MLA Handbook (7th Edition):

Howe, John Andrew. “A New Generation of Mixture-Model Cluster Analysis with Information Complexity and the Genetic EM Algorithm.” 2009. Web. 21 Apr 2019.

Vancouver:

Howe JA. A New Generation of Mixture-Model Cluster Analysis with Information Complexity and the Genetic EM Algorithm. [Internet] [Doctoral dissertation]. University of Tennessee – Knoxville; 2009. [cited 2019 Apr 21]. Available from: https://trace.tennessee.edu/utk_graddiss/863.

Council of Science Editors:

Howe JA. A New Generation of Mixture-Model Cluster Analysis with Information Complexity and the Genetic EM Algorithm. [Doctoral Dissertation]. University of Tennessee – Knoxville; 2009. Available from: https://trace.tennessee.edu/utk_graddiss/863

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