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Technology integration and analysis using boosting and ensemble

Jun, Sunghae - In: Journal of open innovation : technology, market, and … 7 (2021) 1/27, pp. 1-15

technologies. We integrate patent big data for technological integration and use text mining, boosting, and ensemble for integrated … technologies and analyze the integrated patent data using regression trees, random forest, extreme gradient boosting, and ensemble …

Persistent link: https://www.econbiz.de/10012417956

Machine learning-based classifiers ensemble for credit risk assessment

Pandey, Trilok Nath; Jagadev, Alok Kumar; Choudhury, D.; … - In: International journal of electronic finance : IJEF 7 (2013) 3/4, pp. 227-249

Persistent link: https://www.econbiz.de/10010400393

A majority vote based classifier ensemble for web service classification

Qamar, Usman; Niza, Rozina; Bashir, Saba; Khan, Farhan … - In: Business & information systems engineering : BISE ; the … 58 (2016) 4, pp. 249-259

Persistent link: https://www.econbiz.de/10011595258

Selecting classifiers for an ensemble : an integrated ensemble generation procedure

Osei-Bryson, Kweku-Muata - In: Knowledge discovery process and methods to enhance …, (pp. 327-346). 2015

Persistent link: https://www.econbiz.de/10012123358

Super RaSE : super random subspace ensemble classification

Zhu, Jianan; Feng, Yang - In: Journal of risk and financial management : JRFM 14 (2021) 12, pp. 1-18

We propose a new ensemble classification algorithm, named super random subspace ensemble (Super RaSE), to tackle the … sparse classification problem. The proposed algorithm is motivated by the random subspace ensemble algorithm (RaSE). The RaSE …

Persistent link: https://www.econbiz.de/10012799946

A combination of clustering-based under-sampling with ensemble methods for solving imbalanced class problem in intelligent systems

Shahabadi, Mohammad Saleh Ebrahimi; Tabrizchi, Hamed; … - In: Technological forecasting & social change : an … 169 (2021), pp. 1-17

Persistent link: https://www.econbiz.de/10012804555

Building predictive models for feature selection in genomic mining

Figini, Silvia; Giudici, Paolo - 2006

new approach based on marker selection. Finally, we compare the best predictive model with a model derived from a boosting …

Persistent link: https://www.econbiz.de/10010326099

Positive-versus-negative classification for model aggregation in predictive data mining

Lutu, Patricia E. N.; Engelbrecht, Andries P. - In: INFORMS journal on computing : JOC 25 (2013) 4, pp. 792-807

Persistent link: https://www.econbiz.de/10010203574

How health managers can use data mining for predicting individuals' risks of contracting nosocomial pneumonia

Duclos-Gosselin, Louis; Rigaux-Bricmont, Benny; Darmon, … - In: Health marketing quarterly 32 (2015) 1, pp. 1-13

Persistent link: https://www.econbiz.de/10011289349

Big data analytics : a new perspective

Chudik, Alexander; Kapetanios, George; Pesaran, M. Hashem - 2016

Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised...

Persistent link: https://www.econbiz.de/10011444508