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Refinado por: Base de dados/Biblioteca: Institute of Physics (IOP) Journals - HEAL-Link remover assunto: Vorhersagemodell remover Maschinelles Lernen remover
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1
Classification of Imbalanced Data:Review of Methods and Applications
Classification of Imbalanced Data:Review of Methods and Applications
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Classification of Imbalanced Data:Review of Methods and Applications

Kumar, Pradeep ; Bhatnagar, Roheet ; Gaur, Kuntal ; Bhatnagar, Anurag

IOP conference series. Materials Science and Engineering, 2021-03, Vol.1099 (1), p.12077 [Periódico revisado por pares]

Bristol: IOP Publishing

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2
A software defect prediction method based on sampling and integration
A software defect prediction method based on sampling and integration
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A software defect prediction method based on sampling and integration

Shen, Peng ; Ding, Xiaoming ; Mu, Xuyun ; Xu, Jianing

Journal of physics. Conference series, 2021-01, Vol.1732 (1), p.12002 [Periódico revisado por pares]

IOP Publishing

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3
Disruption prediction and model analysis using LightGBM on J-TEXT and HL-2A
Disruption prediction and model analysis using LightGBM on J-TEXT and HL-2A
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Disruption prediction and model analysis using LightGBM on J-TEXT and HL-2A

Zhong, Y ; Zheng, W ; Chen, Z Y ; Xia, F ; Yu, L M ; Wu, Q Q ; Ai, X K ; Shen, C S ; Yang, Z Y ; Yan, W ; Ding, Y H ; Liang, Y F ; Chen, Z P ; Tong, R H ; Bai, W ; Fang, J G ; Li, F

Plasma physics and controlled fusion, 2021-07, Vol.63 (7), p.75008 [Periódico revisado por pares]

IOP Publishing

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4
Deep-learning for seizure forecasting in canines with epilepsy
Deep-learning for seizure forecasting in canines with epilepsy
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Deep-learning for seizure forecasting in canines with epilepsy

Nejedly, Petr ; Kremen, Vaclav ; Sladky, Vladimir ; Nasseri, Mona ; Guragain, Hari ; Klimes, Petr ; Cimbalnik, Jan ; Varatharajah, Yogatheesan ; Brinkmann, Benjamin H ; Worrell, Gregory A

Journal of neural engineering, 2019-06, Vol.16 (3), p.036031-036031 [Periódico revisado por pares]

England: IOP Publishing

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5
Digital twin-driven machine learning: ball bearings fault severity classification
Digital twin-driven machine learning: ball bearings fault severity classification
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Digital twin-driven machine learning: ball bearings fault severity classification

Farhat, Mohamed Habib ; Chiementin, Xavier ; Chaari, Fakher ; Bolaers, Fabrice ; Haddar, Mohamed

Measurement science & technology, 2021-04, Vol.32 (4), p.44006 [Periódico revisado por pares]

IOP Publishing

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6
Understanding and assembling user behaviours using features of Moodle data for eLearning usage from performance of course-student weblog
Understanding and assembling user behaviours using features of Moodle data for eLearning usage from performance of course-student weblog
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Understanding and assembling user behaviours using features of Moodle data for eLearning usage from performance of course-student weblog

Chayanukro, S ; Mahmuddin, M ; Husni, H

Journal of physics. Conference series, 2021-04, Vol.1869 (1), p.12087 [Periódico revisado por pares]

Bristol: IOP Publishing

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7
Assessment of Prediction Models of Confirmed, Recovered and Deceased cases due to COVID-19
Assessment of Prediction Models of Confirmed, Recovered and Deceased cases due to COVID-19
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Assessment of Prediction Models of Confirmed, Recovered and Deceased cases due to COVID-19

Rakshit, P ; Debnath, S ; Mistri, J ; Kumar, S

Journal of physics. Conference series, 2021-02, Vol.1797 (1), p.12004 [Periódico revisado por pares]

Bristol: IOP Publishing

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8
A machine learning model for quantifying the effect of lifestyle interventions for patients with type 2 diabetes mellitus
A machine learning model for quantifying the effect of lifestyle interventions for patients with type 2 diabetes mellitus
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A machine learning model for quantifying the effect of lifestyle interventions for patients with type 2 diabetes mellitus

Bi, Suhuan ; Ding, Xiangqian ; Yu, Shusong ; Guo, Baoqi ; Mu, Liangliang ; Wang, Bin

Journal of physics. Conference series, 2021-01, Vol.1732 (1), p.12006 [Periódico revisado por pares]

IOP Publishing

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9
A review of using data mining and machine learning for predicting drug loading modeling in solid lipid nanoparticles containing curcumin
A review of using data mining and machine learning for predicting drug loading modeling in solid lipid nanoparticles containing curcumin
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A review of using data mining and machine learning for predicting drug loading modeling in solid lipid nanoparticles containing curcumin

Widyati, R ; Ashari, A ; Afiahayati

Journal of physics. Conference series, 2021-06, Vol.1918 (4), p.42015 [Periódico revisado por pares]

Bristol: IOP Publishing

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10
Predicting Student Drop-Out in Higher Institution Using Data Mining Techniques
Predicting Student Drop-Out in Higher Institution Using Data Mining Techniques
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Predicting Student Drop-Out in Higher Institution Using Data Mining Techniques

Wan Yaacob, W F ; Mohd Sobri, N ; Nasir, S A Md ; Wan Yaacob, W F ; Norshahidi, N D ; Wan Husin, W Z

Journal of physics. Conference series, 2020-03, Vol.1496 (1), p.12005 [Periódico revisado por pares]

Bristol: IOP Publishing

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