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You searched for subject:(Feature selection). Showing records 1 – 16 of 16 total matches.

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NSYSU

1. Wang, Po-Cheng. Automatic Attribute Clustering and Feature Selection Based on Genetic Algorithms.

Degree: Master, Computer Science and Engineering, 2009, NSYSU

Feature selection is an important pre-processing step in mining and learning. A good set of features can not only improve the accuracy of classification, but… (more)

Subjects/Keywords: k-means; reduct; genetic algorithms; feature clustering; feature selection

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

APA (6th Edition):

Wang, P. (2009). Automatic Attribute Clustering and Feature Selection Based on Genetic Algorithms. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0821109-092325

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):

Wang, Po-Cheng. “Automatic Attribute Clustering and Feature Selection Based on Genetic Algorithms.” 2009. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0821109-092325.

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

MLA Handbook (7th Edition):

Wang, Po-Cheng. “Automatic Attribute Clustering and Feature Selection Based on Genetic Algorithms.” 2009. Web. 19 Jun 2019.

Vancouver:

Wang P. Automatic Attribute Clustering and Feature Selection Based on Genetic Algorithms. [Internet] [Thesis]. NSYSU; 2009. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0821109-092325.

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

Council of Science Editors:

Wang P. Automatic Attribute Clustering and Feature Selection Based on Genetic Algorithms. [Thesis]. NSYSU; 2009. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0821109-092325

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


NSYSU

2. Chen, Shin-shou. A Study of Multi-objective Genetic Models for Stock Selection.

Degree: Master, Computer Science and Engineering, 2014, NSYSU

 Stock selection has long been recognized as a challenging and important task in finance. Recent advances in machine learning and data mining are leading to… (more)

Subjects/Keywords: genetic algorithms; stock selection; asset allocation; feature selection; multi-objective optimization

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APA (6th Edition):

Chen, S. (2014). A Study of Multi-objective Genetic Models for Stock Selection. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0725114-101833

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):

Chen, Shin-shou. “A Study of Multi-objective Genetic Models for Stock Selection.” 2014. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0725114-101833.

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

MLA Handbook (7th Edition):

Chen, Shin-shou. “A Study of Multi-objective Genetic Models for Stock Selection.” 2014. Web. 19 Jun 2019.

Vancouver:

Chen S. A Study of Multi-objective Genetic Models for Stock Selection. [Internet] [Thesis]. NSYSU; 2014. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0725114-101833.

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

Council of Science Editors:

Chen S. A Study of Multi-objective Genetic Models for Stock Selection. [Thesis]. NSYSU; 2014. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0725114-101833

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


NSYSU

3. Chen, Wei-Yu. Forward-Selection-Based Feature Selection for Genre Analysis and Recognition of Popular Music.

Degree: Master, Electrical Engineering, 2012, NSYSU

 In this thesis, a popular music genre recognition approach for Japanese popular music using SVM (support vector machine) with forward feature selection is proposed. First,… (more)

Subjects/Keywords: RBF (radial basis function); SVM (support vector machine); forward selection; Genre recognition; feature selection

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APA (6th Edition):

Chen, W. (2012). Forward-Selection-Based Feature Selection for Genre Analysis and Recognition of Popular Music. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0909112-110138

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):

Chen, Wei-Yu. “Forward-Selection-Based Feature Selection for Genre Analysis and Recognition of Popular Music.” 2012. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0909112-110138.

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

MLA Handbook (7th Edition):

Chen, Wei-Yu. “Forward-Selection-Based Feature Selection for Genre Analysis and Recognition of Popular Music.” 2012. Web. 19 Jun 2019.

Vancouver:

Chen W. Forward-Selection-Based Feature Selection for Genre Analysis and Recognition of Popular Music. [Internet] [Thesis]. NSYSU; 2012. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0909112-110138.

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

Council of Science Editors:

Chen W. Forward-Selection-Based Feature Selection for Genre Analysis and Recognition of Popular Music. [Thesis]. NSYSU; 2012. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0909112-110138

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


NSYSU

4. Wu, Kuo-yi. GAGS : A Novel Microarray Gene Selection Algorithm for Gene Expression Classification.

Degree: Master, Computer Science and Engineering, 2010, NSYSU

 In this thesis, we have proposed a novel microarray gene selection algorithm consisting of five processes for solving gene expression classification problem. A normalization process… (more)

Subjects/Keywords: Feature selection; Gene expression data analysis; Genetic algorithm

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

APA (6th Edition):

Wu, K. (2010). GAGS : A Novel Microarray Gene Selection Algorithm for Gene Expression Classification. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0730110-230815

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):

Wu, Kuo-yi. “GAGS : A Novel Microarray Gene Selection Algorithm for Gene Expression Classification.” 2010. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0730110-230815.

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

MLA Handbook (7th Edition):

Wu, Kuo-yi. “GAGS : A Novel Microarray Gene Selection Algorithm for Gene Expression Classification.” 2010. Web. 19 Jun 2019.

Vancouver:

Wu K. GAGS : A Novel Microarray Gene Selection Algorithm for Gene Expression Classification. [Internet] [Thesis]. NSYSU; 2010. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0730110-230815.

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

Council of Science Editors:

Wu K. GAGS : A Novel Microarray Gene Selection Algorithm for Gene Expression Classification. [Thesis]. NSYSU; 2010. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0730110-230815

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


NSYSU

5. Wang, Tse-yao. The study of data preprocessing difference to impact the botnet detection performance.

Degree: PhD, Information Management, 2016, NSYSU

 Many studies employ machine learning to detect botnet C&C communications traffic quite effective. If the former data handled properly, it will affect the final detection… (more)

Subjects/Keywords: data transformation; machine learning; Botnet detection; Rough Set Theory; feature selection

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APA (6th Edition):

Wang, T. (2016). The study of data preprocessing difference to impact the botnet detection performance. (Doctoral Dissertation). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613116-112523

Chicago Manual of Style (16th Edition):

Wang, Tse-yao. “The study of data preprocessing difference to impact the botnet detection performance.” 2016. Doctoral Dissertation, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613116-112523.

MLA Handbook (7th Edition):

Wang, Tse-yao. “The study of data preprocessing difference to impact the botnet detection performance.” 2016. Web. 19 Jun 2019.

Vancouver:

Wang T. The study of data preprocessing difference to impact the botnet detection performance. [Internet] [Doctoral dissertation]. NSYSU; 2016. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613116-112523.

Council of Science Editors:

Wang T. The study of data preprocessing difference to impact the botnet detection performance. [Doctoral Dissertation]. NSYSU; 2016. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613116-112523


NSYSU

6. Wu, Jain-Shing. High Specificity Literature Mining Method Based on Microarray Expression Profile for Discovering Hidden Connections among Diseases, Genes, and Drugs.

Degree: PhD, Computer Science and Engineering, 2011, NSYSU

 In recent years, with the microarray technique widely adopted, a large amount of biomedical literatures are published to provide a lot of useful information. However,… (more)

Subjects/Keywords: genetic algorithm; feature selection; Hidden relationship; literature mining; gene expression profile

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

APA (6th Edition):

Wu, J. (2011). High Specificity Literature Mining Method Based on Microarray Expression Profile for Discovering Hidden Connections among Diseases, Genes, and Drugs. (Doctoral Dissertation). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0905111-174611

Chicago Manual of Style (16th Edition):

Wu, Jain-Shing. “High Specificity Literature Mining Method Based on Microarray Expression Profile for Discovering Hidden Connections among Diseases, Genes, and Drugs.” 2011. Doctoral Dissertation, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0905111-174611.

MLA Handbook (7th Edition):

Wu, Jain-Shing. “High Specificity Literature Mining Method Based on Microarray Expression Profile for Discovering Hidden Connections among Diseases, Genes, and Drugs.” 2011. Web. 19 Jun 2019.

Vancouver:

Wu J. High Specificity Literature Mining Method Based on Microarray Expression Profile for Discovering Hidden Connections among Diseases, Genes, and Drugs. [Internet] [Doctoral dissertation]. NSYSU; 2011. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0905111-174611.

Council of Science Editors:

Wu J. High Specificity Literature Mining Method Based on Microarray Expression Profile for Discovering Hidden Connections among Diseases, Genes, and Drugs. [Doctoral Dissertation]. NSYSU; 2011. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0905111-174611


NSYSU

7. Lin, Feng-Shih. Improved Approaches for Attribute Clustering Based on the Group Genetic Algorithm.

Degree: Master, Computer Science and Engineering, 2011, NSYSU

Feature selection is a pre-processing step in data-mining and machine learning, and plays an important role for analyzing high-dimensional data. Appropriately selected features can not… (more)

Subjects/Keywords: feature selection; genetic algorithm; grouping genetic algorithm; data mining; Attribute clustering

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

APA (6th Edition):

Lin, F. (2011). Improved Approaches for Attribute Clustering Based on the Group Genetic Algorithm. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0909111-070933

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):

Lin, Feng-Shih. “Improved Approaches for Attribute Clustering Based on the Group Genetic Algorithm.” 2011. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0909111-070933.

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

MLA Handbook (7th Edition):

Lin, Feng-Shih. “Improved Approaches for Attribute Clustering Based on the Group Genetic Algorithm.” 2011. Web. 19 Jun 2019.

Vancouver:

Lin F. Improved Approaches for Attribute Clustering Based on the Group Genetic Algorithm. [Internet] [Thesis]. NSYSU; 2011. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0909111-070933.

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

Council of Science Editors:

Lin F. Improved Approaches for Attribute Clustering Based on the Group Genetic Algorithm. [Thesis]. NSYSU; 2011. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0909111-070933

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


NSYSU

8. Lin, Ji-Wei. Selection of the most informative schemes for multi-locus sequence typing.

Degree: Master, Institute Of Medical Science And Technology, 2018, NSYSU

 To investigate and surveillance the foodborne disease outbreak caused by bacteria, molecular sequence subtyping method would be employed. In our study, we build an open-access… (more)

Subjects/Keywords: Feature selection; Molecular subtyping; Typing scheme selection; Foodborne disease; Whole-genome multilocus sequence typing (wgMLST); Next generation sequencing (NGS)

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

APA (6th Edition):

Lin, J. (2018). Selection of the most informative schemes for multi-locus sequence typing. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0631118-141016

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):

Lin, Ji-Wei. “Selection of the most informative schemes for multi-locus sequence typing.” 2018. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0631118-141016.

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

MLA Handbook (7th Edition):

Lin, Ji-Wei. “Selection of the most informative schemes for multi-locus sequence typing.” 2018. Web. 19 Jun 2019.

Vancouver:

Lin J. Selection of the most informative schemes for multi-locus sequence typing. [Internet] [Thesis]. NSYSU; 2018. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0631118-141016.

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

Council of Science Editors:

Lin J. Selection of the most informative schemes for multi-locus sequence typing. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0631118-141016

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


NSYSU

9. Hor, Chiou-Yi. Machine Learning Approaches for the Protein and RNA Sequence Analysis.

Degree: PhD, Computer Science and Engineering, 2014, NSYSU

 The machine learning approach has been adopted in bioinformatics for several decades. Given a sequence, which may be composed of nucleotides or amino acids, the… (more)

Subjects/Keywords: feature selection; RNA secondary structure; essential protein; support vector machine; bioinformatics; machine learning

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

APA (6th Edition):

Hor, C. (2014). Machine Learning Approaches for the Protein and RNA Sequence Analysis. (Doctoral Dissertation). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0709114-104627

Chicago Manual of Style (16th Edition):

Hor, Chiou-Yi. “Machine Learning Approaches for the Protein and RNA Sequence Analysis.” 2014. Doctoral Dissertation, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0709114-104627.

MLA Handbook (7th Edition):

Hor, Chiou-Yi. “Machine Learning Approaches for the Protein and RNA Sequence Analysis.” 2014. Web. 19 Jun 2019.

Vancouver:

Hor C. Machine Learning Approaches for the Protein and RNA Sequence Analysis. [Internet] [Doctoral dissertation]. NSYSU; 2014. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0709114-104627.

Council of Science Editors:

Hor C. Machine Learning Approaches for the Protein and RNA Sequence Analysis. [Doctoral Dissertation]. NSYSU; 2014. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0709114-104627


NSYSU

10. Su , Yen-Ting. TAIEX Trend Prediction with Support Vector Machine.

Degree: Master, Finance, 2016, NSYSU

 This paper develops a prediction model which combined genetic algorithms and support vector machine to predict the five-day-ahead direction of the TAIEX. We employ technical… (more)

Subjects/Keywords: Genetic algorithms; Technical indicators; Stock prediction; Feature selection; Support vector machine; Machine learning

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

APA (6th Edition):

Su , Y. (2016). TAIEX Trend Prediction with Support Vector Machine. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0609115-123653

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):

Su , Yen-Ting. “TAIEX Trend Prediction with Support Vector Machine.” 2016. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0609115-123653.

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

MLA Handbook (7th Edition):

Su , Yen-Ting. “TAIEX Trend Prediction with Support Vector Machine.” 2016. Web. 19 Jun 2019.

Vancouver:

Su Y. TAIEX Trend Prediction with Support Vector Machine. [Internet] [Thesis]. NSYSU; 2016. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0609115-123653.

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

Council of Science Editors:

Su Y. TAIEX Trend Prediction with Support Vector Machine. [Thesis]. NSYSU; 2016. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0609115-123653

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


NSYSU

11. Liao, Ting-Yi. Detecting Near-Duplicate Documents using Sentence-Level Features and Machine Learning.

Degree: Master, Electrical Engineering, 2012, NSYSU

 From the large scale of documents effective to find the near-duplicate document, has been a very important issue. In this paper, we propose a new… (more)

Subjects/Keywords: Near-duplicate; threshold; trial-and-error; support vector machine; feature selection; stop words; similarity function

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

APA (6th Edition):

Liao, T. (2012). Detecting Near-Duplicate Documents using Sentence-Level Features and Machine Learning. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1023112-100138

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):

Liao, Ting-Yi. “Detecting Near-Duplicate Documents using Sentence-Level Features and Machine Learning.” 2012. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1023112-100138.

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

MLA Handbook (7th Edition):

Liao, Ting-Yi. “Detecting Near-Duplicate Documents using Sentence-Level Features and Machine Learning.” 2012. Web. 19 Jun 2019.

Vancouver:

Liao T. Detecting Near-Duplicate Documents using Sentence-Level Features and Machine Learning. [Internet] [Thesis]. NSYSU; 2012. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1023112-100138.

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

Council of Science Editors:

Liao T. Detecting Near-Duplicate Documents using Sentence-Level Features and Machine Learning. [Thesis]. NSYSU; 2012. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1023112-100138

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


NSYSU

12. Mi, Jung-Chun. Constructing Call Warrant Trading Strategies with Deep Learning in Taiwan.

Degree: Master, Finance, 2018, NSYSU

 This study uses all call warrants from 2003 to 2017 in Taiwan to design trading strategy about Bollinger Bands ,breakouts and moving averages, and then… (more)

Subjects/Keywords: Learning vector quantization; Deep learning; Random forest; Call warrant; Technical analysis; Feature selection

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APA (6th Edition):

Mi, J. (2018). Constructing Call Warrant Trading Strategies with Deep Learning in Taiwan. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0605118-153511

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):

Mi, Jung-Chun. “Constructing Call Warrant Trading Strategies with Deep Learning in Taiwan.” 2018. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0605118-153511.

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

MLA Handbook (7th Edition):

Mi, Jung-Chun. “Constructing Call Warrant Trading Strategies with Deep Learning in Taiwan.” 2018. Web. 19 Jun 2019.

Vancouver:

Mi J. Constructing Call Warrant Trading Strategies with Deep Learning in Taiwan. [Internet] [Thesis]. NSYSU; 2018. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0605118-153511.

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

Council of Science Editors:

Mi J. Constructing Call Warrant Trading Strategies with Deep Learning in Taiwan. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0605118-153511

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


NSYSU

13. Yang, Tun-Hsiang. Air Visibility Forecasting via Artificial Neural Networks and Feature Selection Techniques.

Degree: Master, Mechanical and Electro-Mechanical Engineering, 2003, NSYSU

none Advisors/Committee Members: Chi-Cheng Cheng (chair), Chen-Wen Yen (committee member), Chung-Shin Yuan (chair).

Subjects/Keywords: feature selection; neural network; network; forecasting; visibility

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

APA (6th Edition):

Yang, T. (2003). Air Visibility Forecasting via Artificial Neural Networks and Feature Selection Techniques. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0801103-170540

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):

Yang, Tun-Hsiang. “Air Visibility Forecasting via Artificial Neural Networks and Feature Selection Techniques.” 2003. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0801103-170540.

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

MLA Handbook (7th Edition):

Yang, Tun-Hsiang. “Air Visibility Forecasting via Artificial Neural Networks and Feature Selection Techniques.” 2003. Web. 19 Jun 2019.

Vancouver:

Yang T. Air Visibility Forecasting via Artificial Neural Networks and Feature Selection Techniques. [Internet] [Thesis]. NSYSU; 2003. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0801103-170540.

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

Council of Science Editors:

Yang T. Air Visibility Forecasting via Artificial Neural Networks and Feature Selection Techniques. [Thesis]. NSYSU; 2003. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0801103-170540

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


NSYSU

14. Lin, Yung-Shen. Measuring Document Similarity Based on Text Classification and Clustering.

Degree: PhD, Institute of Electrical Engineering, 2013, NSYSU

 This thesis proposes a novel similarity measure that applies between documents. The proposed measure is also extended to gauge the similarity between two sets of… (more)

Subjects/Keywords: similarity function; feature selection; entropy; document clustering; document classification; near-duplicate document; accuracy; classifiers; clustering algorithms

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

APA (6th Edition):

Lin, Y. (2013). Measuring Document Similarity Based on Text Classification and Clustering. (Doctoral Dissertation). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0425113-122452

Chicago Manual of Style (16th Edition):

Lin, Yung-Shen. “Measuring Document Similarity Based on Text Classification and Clustering.” 2013. Doctoral Dissertation, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0425113-122452.

MLA Handbook (7th Edition):

Lin, Yung-Shen. “Measuring Document Similarity Based on Text Classification and Clustering.” 2013. Web. 19 Jun 2019.

Vancouver:

Lin Y. Measuring Document Similarity Based on Text Classification and Clustering. [Internet] [Doctoral dissertation]. NSYSU; 2013. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0425113-122452.

Council of Science Editors:

Lin Y. Measuring Document Similarity Based on Text Classification and Clustering. [Doctoral Dissertation]. NSYSU; 2013. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0425113-122452


NSYSU

15. Chang, Yu-Hsiu. Discovery of Evolution Patterns from Sequences of Documents.

Degree: Master, Information Management, 2001, NSYSU

 Due to the ever-increasing volume of textual documents, text mining is a rapidly growing application of knowledge discovery in databases. Past text mining techniques predominately… (more)

Subjects/Keywords: Feature Extraction; Feature Selection; Document Clustering; Frequent Temporal Patterns; Feature-Based Evolution Patterns; Text Mining

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

APA (6th Edition):

Chang, Y. (2001). Discovery of Evolution Patterns from Sequences of Documents. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0806101-111117

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, Yu-Hsiu. “Discovery of Evolution Patterns from Sequences of Documents.” 2001. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0806101-111117.

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

MLA Handbook (7th Edition):

Chang, Yu-Hsiu. “Discovery of Evolution Patterns from Sequences of Documents.” 2001. Web. 19 Jun 2019.

Vancouver:

Chang Y. Discovery of Evolution Patterns from Sequences of Documents. [Internet] [Thesis]. NSYSU; 2001. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0806101-111117.

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

Council of Science Editors:

Chang Y. Discovery of Evolution Patterns from Sequences of Documents. [Thesis]. NSYSU; 2001. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0806101-111117

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


NSYSU

16. Lai, Po-Chuan. Operational Knowledge Acquisition of Refuse Incinerator Using Data Mining Techniques.

Degree: Master, Marine Environment and Engineering, 2005, NSYSU

 The physical and chemical mechanisms in a refuse ncinerator are complex. It is difficult to make a full comprehension of the system without a thorough… (more)

Subjects/Keywords: Decision Tree Classification; Refuse Incinerator; Classification Analysis; Feature Selection; Data Mining

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

APA (6th Edition):

Lai, P. (2005). Operational Knowledge Acquisition of Refuse Incinerator Using Data Mining Techniques. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0805105-001510

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):

Lai, Po-Chuan. “Operational Knowledge Acquisition of Refuse Incinerator Using Data Mining Techniques.” 2005. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0805105-001510.

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

MLA Handbook (7th Edition):

Lai, Po-Chuan. “Operational Knowledge Acquisition of Refuse Incinerator Using Data Mining Techniques.” 2005. Web. 19 Jun 2019.

Vancouver:

Lai P. Operational Knowledge Acquisition of Refuse Incinerator Using Data Mining Techniques. [Internet] [Thesis]. NSYSU; 2005. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0805105-001510.

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

Council of Science Editors:

Lai P. Operational Knowledge Acquisition of Refuse Incinerator Using Data Mining Techniques. [Thesis]. NSYSU; 2005. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0805105-001510

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

.