Micro-averaged performance scores for all classification tools, over the three broader classes in the MHH data set.

Classification performance of MLPD and SLPD.

Guan Yu (562832)
Yufeng Liu (307498)
Kim-Han Thung (562833)
Dinggang Shen (204274)

May 2014

(For MLPD, all the available data are used. For SLPD, only the MRI features are used. The best va...

Average Rankings of the classification algorithms for both synchronous and self-paced datasets.

Hossein Bashashati (757755)
Rabab K. Ward (757756)
Gary E. Birch (757757)
Ali Bashashati (757758)

June 2015

The number in the parenthesis corresponds to the average rank of the algorithm among different su...

Classification performance in the Labyrinth Oddball scenario.

Elsa Andrea Kirchner (497996)
Su Kyoung Kim (497997)
Sirko Straube (497998)
Anett Seeland (497999)
Hendrik Wöhrle (498000)
Mario Michael Krell (498001)
Marc Tabie (498002)
Manfred Fahle (272617)

December 2013

For each subject for a window from to ms the evaluated classification performance and statistic...

Micro-averaged performance scores for all classification tools, over the three broader classes in the VCEP-HL data set.

Damianos P. Melidis (13840436)
Christian Landgraf (13840439)
Gunnar Schmidt (2192308)
Anja Schöner-Heinisch (13840442)
Sandra von Hardenberg (6476750)
Anke Lesinski-Schiedat (9122630)
Wolfgang Nejdl (13840445)
Bernd Auber (4796445)

September 2022

Best values of a performance score, across all classification tools, are shown in bold.</p

The performance of different classifiers associated with the attribute selection methods assessed.

Camila Viana Vieira Farhate (4827780)
Zigomar Menezes de Souza (4827795)
Stanley Robson de Medeiros Oliveira (4827789)
Rose Luiza Moraes Tavares (4919512)
João Luís Nunes Carvalho (4827792)

March 2018

The performance of different classifiers associated with the attribute selection methods assessed...

Performance scores of MGH/MF waveform database grouped by average heart rate (HR).

Qiong Yu (446491)
Aili Liu (1540255)
Tiebing Liu (771588)
Yuwei Mao (6523562)
Wei Chen (23863)
Hongxing Liu (1582783)

March 2019

Performance scores of MGH/MF waveform database grouped by average heart rate (HR).</p

Micro-average classification accuracy of ML classifiers bs. Baseline for comparisons A to F.

Vassiliki Rentoumi (3853855)
Timothy Peters (3490379)
Jonathan Conlin (3853861)
Peter Garrard (3853858)

March 2017

Micro-average classification accuracy of ML classifiers bs. Baseline for comparisons A to F.</p

The classification performances of the 3 best classifiers for the 3 datasets.

Ning Zhang (23771)
You Zhou (129411)
Tao Huang (110613)
Yu-Chao Zhang (512666)
Bi-Qing Li (137162)
Lei Chen (54296)
Yu-Dong Cai (133116)

September 2014

The classification performances of the 3 best classifiers for the 3 datasets.</p

Average Rankings of the classification algorithms for binary and multi-class classification in synchronous datasets.

Hossein Bashashati (757755)
Rabab K. Ward (757756)
Gary E. Birch (757757)
Ali Bashashati (757758)

June 2015

The number of subjects in binary task was 12 and the number of subjects in multi-task BCIs was 9....

The performance comparison results for the three different classifiers using four indexes.

Lili Chen (66681)
Yaru Hao (6593603)
Xue Hu (3309012)

April 2019

The performance comparison results for the three different classifiers using four indexes.</p

Precision-recall curves and AUC scores of all classification tools for the MHH data set.

Damianos P. Melidis (13840436)
Christian Landgraf (13840439)
Gunnar Schmidt (2192308)
Anja Schöner-Heinisch (13840442)
Sandra von Hardenberg (6476750)
Anke Lesinski-Schiedat (9122630)
Wolfgang Nejdl (13840445)
Bernd Auber (4796445)

September 2022

(A) Prediction of “Benign” broader class versus “Pathogenic” broader class and “VUS” class (B) Predi...

Rankings of existing best performing classifier (LSVM) and AdaBoost ensemble classifiers, based on Kendall’s W test results using the MDDR dataset by specificity measure.

Lateefat Temitope Afolabi (4762959)
Faisal Saeed (427323)
Haslinda Hashim (4762962)
Olutomilayo Olayemi Petinrin (4762965)

January 2018

Rankings of existing best performing classifier (LSVM) and AdaBoost ensemble classifiers, based o...

Comparison of performance of individual and combined classifiers.

ManChon U (553999)
Eric Talevich (235366)
Samiksha Katiyar (379207)
Khaled Rasheed (554000)
Natarajan Kannan (41300)

April 2014

Each algorithm trained using selected features and evaluated with 10-fold cross-validation. Value...

Comparative performance analysis of the rule-based classifiers on Dataset 4, respectively (at 4-fold CVs repeating for 10 times); where bold font denotes the highest value for each column.

Ujjwal Maulik (169015)
Saurav Mallik (441729)
Anirban Mukhopadhyay (169006)
Sanghamitra Bandyopadhyay (169021)

April 2015

Comparative performance analysis of the rule-based classifiers on Dataset 4, respectively (at 4-f...

Comparative performance analysis of the rule-based classifiers on Dataset 1, respectively (at 4-fold CVs repeating for 10 times); where bold font denotes the highest value for each column.

Ujjwal Maulik (169015)
Saurav Mallik (441729)
Anirban Mukhopadhyay (169006)
Sanghamitra Bandyopadhyay (169021)

April 2015

Comparative performance analysis of the rule-based classifiers on Dataset 1, respectively (at 4-f...

Classification performance of MLPD and SLPD.

Guan Yu (562832)
Yufeng Liu (307498)
Kim-Han Thung (562833)
Dinggang Shen (204274)

May 2014

(For MLPD, all the available data are used. For SLPD, only the MRI features are used. The best va...

Average Rankings of the classification algorithms for both synchronous and self-paced datasets.

Hossein Bashashati (757755)
Rabab K. Ward (757756)
Gary E. Birch (757757)
Ali Bashashati (757758)

June 2015

The number in the parenthesis corresponds to the average rank of the algorithm among different su...

Classification performance in the Labyrinth Oddball scenario.

Elsa Andrea Kirchner (497996)
Su Kyoung Kim (497997)
Sirko Straube (497998)
Anett Seeland (497999)
Hendrik Wöhrle (498000)
Mario Michael Krell (498001)
Marc Tabie (498002)
Manfred Fahle (272617)

December 2013

For each subject for a window from to ms the evaluated classification performance and statistic...

Micro-averaged performance scores for all classification tools, over the three broader classes in the VCEP-HL data set.

Damianos P. Melidis (13840436)
Christian Landgraf (13840439)
Gunnar Schmidt (2192308)
Anja Schöner-Heinisch (13840442)
Sandra von Hardenberg (6476750)
Anke Lesinski-Schiedat (9122630)
Wolfgang Nejdl (13840445)
Bernd Auber (4796445)

September 2022

Best values of a performance score, across all classification tools, are shown in bold.</p

The performance of different classifiers associated with the attribute selection methods assessed.

Camila Viana Vieira Farhate (4827780)
Zigomar Menezes de Souza (4827795)
Stanley Robson de Medeiros Oliveira (4827789)
Rose Luiza Moraes Tavares (4919512)
João Luís Nunes Carvalho (4827792)

March 2018

The performance of different classifiers associated with the attribute selection methods assessed...

Performance scores of MGH/MF waveform database grouped by average heart rate (HR).

Qiong Yu (446491)
Aili Liu (1540255)
Tiebing Liu (771588)
Yuwei Mao (6523562)
Wei Chen (23863)
Hongxing Liu (1582783)

March 2019

Performance scores of MGH/MF waveform database grouped by average heart rate (HR).</p

Micro-average classification accuracy of ML classifiers bs. Baseline for comparisons A to F.

Vassiliki Rentoumi (3853855)
Timothy Peters (3490379)
Jonathan Conlin (3853861)
Peter Garrard (3853858)

March 2017

Micro-average classification accuracy of ML classifiers bs. Baseline for comparisons A to F.</p

The classification performances of the 3 best classifiers for the 3 datasets.

Ning Zhang (23771)
You Zhou (129411)
Tao Huang (110613)
Yu-Chao Zhang (512666)
Bi-Qing Li (137162)
Lei Chen (54296)
Yu-Dong Cai (133116)

September 2014

The classification performances of the 3 best classifiers for the 3 datasets.</p

Average Rankings of the classification algorithms for binary and multi-class classification in synchronous datasets.

Hossein Bashashati (757755)
Rabab K. Ward (757756)
Gary E. Birch (757757)
Ali Bashashati (757758)

June 2015

The number of subjects in binary task was 12 and the number of subjects in multi-task BCIs was 9....

The performance comparison results for the three different classifiers using four indexes.

Lili Chen (66681)
Yaru Hao (6593603)
Xue Hu (3309012)

April 2019

The performance comparison results for the three different classifiers using four indexes.</p

Precision-recall curves and AUC scores of all classification tools for the MHH data set.

Damianos P. Melidis (13840436)
Christian Landgraf (13840439)
Gunnar Schmidt (2192308)
Anja Schöner-Heinisch (13840442)
Sandra von Hardenberg (6476750)
Anke Lesinski-Schiedat (9122630)
Wolfgang Nejdl (13840445)
Bernd Auber (4796445)

September 2022

(A) Prediction of “Benign” broader class versus “Pathogenic” broader class and “VUS” class (B) Predi...

Rankings of existing best performing classifier (LSVM) and AdaBoost ensemble classifiers, based on Kendall’s W test results using the MDDR dataset by specificity measure.

Lateefat Temitope Afolabi (4762959)
Faisal Saeed (427323)
Haslinda Hashim (4762962)
Olutomilayo Olayemi Petinrin (4762965)

January 2018

Rankings of existing best performing classifier (LSVM) and AdaBoost ensemble classifiers, based o...

Comparison of performance of individual and combined classifiers.

ManChon U (553999)
Eric Talevich (235366)
Samiksha Katiyar (379207)
Khaled Rasheed (554000)
Natarajan Kannan (41300)

April 2014

Each algorithm trained using selected features and evaluated with 10-fold cross-validation. Value...

Comparative performance analysis of the rule-based classifiers on Dataset 4, respectively (at 4-fold CVs repeating for 10 times); where bold font denotes the highest value for each column.

Ujjwal Maulik (169015)
Saurav Mallik (441729)
Anirban Mukhopadhyay (169006)
Sanghamitra Bandyopadhyay (169021)

April 2015

Comparative performance analysis of the rule-based classifiers on Dataset 4, respectively (at 4-f...

Comparative performance analysis of the rule-based classifiers on Dataset 1, respectively (at 4-fold CVs repeating for 10 times); where bold font denotes the highest value for each column.

Ujjwal Maulik (169015)
Saurav Mallik (441729)
Anirban Mukhopadhyay (169006)
Sanghamitra Bandyopadhyay (169021)

April 2015

Comparative performance analysis of the rule-based classifiers on Dataset 1, respectively (at 4-f...

Classification performance of MLPD and SLPD.

Guan Yu (562832)
Yufeng Liu (307498)
Kim-Han Thung (562833)
Dinggang Shen (204274)

May 2014

(For MLPD, all the available data are used. For SLPD, only the MRI features are used. The best va...

Average Rankings of the classification algorithms for both synchronous and self-paced datasets.

Hossein Bashashati (757755)
Rabab K. Ward (757756)
Gary E. Birch (757757)
Ali Bashashati (757758)

June 2015

The number in the parenthesis corresponds to the average rank of the algorithm among different su...

Classification performance in the Labyrinth Oddball scenario.

Elsa Andrea Kirchner (497996)
Su Kyoung Kim (497997)
Sirko Straube (497998)
Anett Seeland (497999)
Hendrik Wöhrle (498000)
Mario Michael Krell (498001)
Marc Tabie (498002)
Manfred Fahle (272617)

December 2013

For each subject for a window from to ms the evaluated classification performance and statistic...

Micro-averaged performance scores for all classification tools, over the three broader classes in the MHH data set.

Abstract

Extracted data

Micro-averaged performance scores for all classification tools, over the three broader classes in the MHH data set.

Abstract

Extracted data

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