The performance comparison of the models trained with different sequence lengths.

Performance comparison of CNN models with different region sizes and other baseline models.

Hong-Jie Dai (36448)
Jitendra Jonnagaddala (5859893)

October 2018

Performance comparison of CNN models with different region sizes and other baseline models.</p

Comparison of the performance of our models with that of LACE, assuming a 25% intervention rate.

Mehdi Jamei (4249108)
Aleksandr Nisnevich (4249099)
Everett Wetchler (4249105)
Sylvia Sudat (4249111)
Eric Liu (4249102)

July 2017

Comparison of the performance of our models with that of LACE, assuming a 25% intervention rate.<...

Performance of machine learning models on test set using the original imbalanced training set.

Nirajan Budhathoki (17599014)
Ramesh Bhandari (11080476)
Suraj Bashyal (17599017)
Carl Lee (17599020)

December 2023

Performance of machine learning models on test set using the original imbalanced training set.</p

The performance comparison of TempSeq-Net model for prediction with different sequence lengths.

Jiewei Jiang (3845005)
Xiyang Liu (3226269)
Lin Liu (74495)
Shuai Wang (109515)
Erping Long (822849)
Haoqing Yang (2900903)
Fuqiang Yuan (3721129)
Deying Yu (5575121)
Kai Zhang (102844)
Liming Wang (114648)
Zhenzhen Liu (333682)
Dongni Wang (753154)
Changzun Xi (5575124)
Zhuoling Lin (406545)
Xiaohang Wu (609779)
Jiangtao Cui (3845002)
Mingmin Zhu (3845008)
Haotian Lin (82598)

July 2018

The performance comparison of TempSeq-Net model for prediction with different sequence lengths.</...

Comparing performance of the proposed methods built with different number of individual models.

Lucy Nwosu (14129241)
Xiangfang Li (1628737)
Lijun Qian (2364427)
Seungchan Kim (292997)
Xishuang Dong (6658961)

November 2022

Comparing performance of the proposed methods built with different number of individual models.</p

A Statistical model comparison in training the models when P = 105 and Q = 27.

Monowar Hossain (5150648)
Saad Mekhilef (724278)
Firdaus Afifi (3112299)
Laith M. Halabi (5150651)
Lanre Olatomiwa (5150660)
Mehdi Seyedmahmoudian (5150663)
Ben Horan (5150654)
Alex Stojcevski (5150657)

April 2018

A Statistical model comparison in training the models when P = 105 and Q = 27.</p

Comparison of the measurements between the three models, for each measurement.

Frits A. Rangel (392221)
Thomas J. J. Maal (356232)
Ewald M. Bronkhorst (144659)
K. Hero Breuning (356233)
Jan G. J. H. Schols (392222)
Stefaan J. Bergé (144662)
Anne Marie Kuijpers-Jagtman (144666)

March 2013

Comparison of the measurements between the three models, for each measurement.</p

Performance comparisons between three different models using breast cancer datasets.

Xiaoqian Jiang (124514)
Aditya Menon (124518)
Shuang Wang (46453)
Jihoon Kim (10090)
Lucila Ohno-Machado (3907)

November 2012

Performance comparisons between three different models using breast cancer datasets.</p

Performance comparison between the second on the list and the first and last on the list, by gender and test subject.

Francesca Borgonovi (2270086)
Maciej Jakubowski (5309582)
Artur Pokropek (2270083)

May 2018

Performance comparison between the second on the list and the first and last on the list, by gend...

Performance comparison of a species-specific predictor using the test dataset.

Md. Mehedi Hasan (755447)
Hiroyuki Kurata (35718)

October 2018

Performance comparison of a species-specific predictor using the test dataset.</p

Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cross validation.

Lina Zhang (112887)
Chengjin Zhang (548663)
Rui Gao (247606)
Runtao Yang (697712)
Qing Song (77132)

September 2016

Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...

Performance statistics of the tested algorithms at different activity levels.

Fuad A. Ghaleb (5993252)
Maznah Bte Kamat (5993255)
Mazleena Salleh (3383588)
Mohd Foad Rohani (782460)
Shukor Abd Razak (3383591)

November 2018

Performance statistics of the tested algorithms at different activity levels.</p

The performance of the proposed model at two extreme thresholds with different sparsity.

Junmei Feng (5782550)
Xiaoyi Fengs (5782553)
Ning Zhang (23771)
Jinye Peng (5782556)

September 2018

The performance of the proposed model at two extreme thresholds with different sparsity.</p

Performance comparison among various types of sequence features and methods for the novel-germline prediction.

Chyn Liaw (290346)
Chun-Wei Tung (52367)
Shinn-Ying Ho (52368)

February 2013

Performance comparison among various types of sequence features and methods for the novel-germlin...

The performances of the different classification algorithms as a function of the number of trials.

Aya Kabbara (844823)
Mohamad Khalil (797029)
Wassim El-Falou (844824)
Hassan Eid (844825)
Mahmoud Hassan (614112)

January 2016

The performances of the different classification algorithms as a function of the number of trials...

Performance comparison of CNN models with different region sizes and other baseline models.

Hong-Jie Dai (36448)
Jitendra Jonnagaddala (5859893)

October 2018

Performance comparison of CNN models with different region sizes and other baseline models.</p

Comparison of the performance of our models with that of LACE, assuming a 25% intervention rate.

Mehdi Jamei (4249108)
Aleksandr Nisnevich (4249099)
Everett Wetchler (4249105)
Sylvia Sudat (4249111)
Eric Liu (4249102)

July 2017

Comparison of the performance of our models with that of LACE, assuming a 25% intervention rate.<...

Performance of machine learning models on test set using the original imbalanced training set.

Nirajan Budhathoki (17599014)
Ramesh Bhandari (11080476)
Suraj Bashyal (17599017)
Carl Lee (17599020)

December 2023

Performance of machine learning models on test set using the original imbalanced training set.</p

The performance comparison of TempSeq-Net model for prediction with different sequence lengths.

Jiewei Jiang (3845005)
Xiyang Liu (3226269)
Lin Liu (74495)
Shuai Wang (109515)
Erping Long (822849)
Haoqing Yang (2900903)
Fuqiang Yuan (3721129)
Deying Yu (5575121)
Kai Zhang (102844)
Liming Wang (114648)
Zhenzhen Liu (333682)
Dongni Wang (753154)
Changzun Xi (5575124)
Zhuoling Lin (406545)
Xiaohang Wu (609779)
Jiangtao Cui (3845002)
Mingmin Zhu (3845008)
Haotian Lin (82598)

July 2018

The performance comparison of TempSeq-Net model for prediction with different sequence lengths.</...

Comparing performance of the proposed methods built with different number of individual models.

Lucy Nwosu (14129241)
Xiangfang Li (1628737)
Lijun Qian (2364427)
Seungchan Kim (292997)
Xishuang Dong (6658961)

November 2022

Comparing performance of the proposed methods built with different number of individual models.</p

A Statistical model comparison in training the models when P = 105 and Q = 27.

Monowar Hossain (5150648)
Saad Mekhilef (724278)
Firdaus Afifi (3112299)
Laith M. Halabi (5150651)
Lanre Olatomiwa (5150660)
Mehdi Seyedmahmoudian (5150663)
Ben Horan (5150654)
Alex Stojcevski (5150657)

April 2018

A Statistical model comparison in training the models when P = 105 and Q = 27.</p

Comparison of the measurements between the three models, for each measurement.

Frits A. Rangel (392221)
Thomas J. J. Maal (356232)
Ewald M. Bronkhorst (144659)
K. Hero Breuning (356233)
Jan G. J. H. Schols (392222)
Stefaan J. Bergé (144662)
Anne Marie Kuijpers-Jagtman (144666)

March 2013

Comparison of the measurements between the three models, for each measurement.</p

Performance comparisons between three different models using breast cancer datasets.

Xiaoqian Jiang (124514)
Aditya Menon (124518)
Shuang Wang (46453)
Jihoon Kim (10090)
Lucila Ohno-Machado (3907)

November 2012

Performance comparisons between three different models using breast cancer datasets.</p

Performance comparison between the second on the list and the first and last on the list, by gender and test subject.

Francesca Borgonovi (2270086)
Maciej Jakubowski (5309582)
Artur Pokropek (2270083)

May 2018

Performance comparison between the second on the list and the first and last on the list, by gend...

Performance comparison of a species-specific predictor using the test dataset.

Md. Mehedi Hasan (755447)
Hiroyuki Kurata (35718)

October 2018

Performance comparison of a species-specific predictor using the test dataset.</p

Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cross validation.

Lina Zhang (112887)
Chengjin Zhang (548663)
Rui Gao (247606)
Runtao Yang (697712)
Qing Song (77132)

September 2016

Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...

Performance statistics of the tested algorithms at different activity levels.

Fuad A. Ghaleb (5993252)
Maznah Bte Kamat (5993255)
Mazleena Salleh (3383588)
Mohd Foad Rohani (782460)
Shukor Abd Razak (3383591)

November 2018

Performance statistics of the tested algorithms at different activity levels.</p

The performance of the proposed model at two extreme thresholds with different sparsity.

Junmei Feng (5782550)
Xiaoyi Fengs (5782553)
Ning Zhang (23771)
Jinye Peng (5782556)

September 2018

The performance of the proposed model at two extreme thresholds with different sparsity.</p

Performance comparison among various types of sequence features and methods for the novel-germline prediction.

Chyn Liaw (290346)
Chun-Wei Tung (52367)
Shinn-Ying Ho (52368)

February 2013

Performance comparison among various types of sequence features and methods for the novel-germlin...

The performances of the different classification algorithms as a function of the number of trials.

Aya Kabbara (844823)
Mohamad Khalil (797029)
Wassim El-Falou (844824)
Hassan Eid (844825)
Mahmoud Hassan (614112)

January 2016

The performances of the different classification algorithms as a function of the number of trials...

Performance comparison of CNN models with different region sizes and other baseline models.

Hong-Jie Dai (36448)
Jitendra Jonnagaddala (5859893)

October 2018

Performance comparison of CNN models with different region sizes and other baseline models.</p

Comparison of the performance of our models with that of LACE, assuming a 25% intervention rate.

Mehdi Jamei (4249108)
Aleksandr Nisnevich (4249099)
Everett Wetchler (4249105)
Sylvia Sudat (4249111)
Eric Liu (4249102)

July 2017

Comparison of the performance of our models with that of LACE, assuming a 25% intervention rate.<...

Performance of machine learning models on test set using the original imbalanced training set.

Nirajan Budhathoki (17599014)
Ramesh Bhandari (11080476)
Suraj Bashyal (17599017)
Carl Lee (17599020)

December 2023

Performance of machine learning models on test set using the original imbalanced training set.</p

The performance comparison of the models trained with different sequence lengths.

Abstract

Extracted data

The performance comparison of the models trained with different sequence lengths.

Abstract

Extracted data

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