Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Hong Kuan Sok"'
Publikováno v:
Pattern Recognition. 50:195-209
Decision trees are comprehensible, but at the cost of a relatively lower prediction accuracy compared to other powerful black-box classifiers such as SVMs. Boosting has been a popular strategy to create an ensemble of decision trees to improve their
Publikováno v:
Pattern Recognition Letters. :57-64
Alternating decision tree (ADTree) brings interpretability to boosting.A novel sparse version of multivariate ADTree is presented.Sparse ADTree is a better generalization of existing univariate ADTree.The decision nodes are designed based on modified
Publikováno v:
Engineering Applications of Artificial Intelligence. 26:1029-1043
The International Technology Roadmap for Semiconductors (ITRS) identifies production test data as an essential element in improving design and technology in the manufacturing process feedback loop. One of the observations made from the high-volume pr
Autor:
Taiwo Adetiloye, Sondipon Adhikari, Ibrahim Aljarah, Senjian An, Serdar Aslan, Anjali Awasthi, Ashish Bakshi, Mohammed Bennamoun, Selami Beyhan, Vimal Bhatia, Gautam Bhattacharya, Alirezah Bosaghzadeh, Farid Boussaid, Dieu Tien Bui, Kien-Trinh Thi Bui, Quang-Thanh Bui, Anusheema Chakraborty, Tanmoy Chatterjee, Rajib Chowdhury, Alan Crosky, Sarat Kumar Das, Pradipta K. Dash, Rajashree Dash, Babette Dellen, Serge Demidenko, Vahdettin Demir, Murat Diker, Erdem Dilmen, Chinh Van Doan, Fadi Dornaika, Nikoo Fakhari, Hossam Faris, Robert B. Fisher, Amir H. Gandomi, Raoof Gholami, Kuntal Ghosh, Nhat-Duc Hoang, Renae Hovey, Farzad Husain, Ioanna Ilia, Peng Jiang, Pawan K. Joshi, Taskin Kavzoglu, Gary Kendrick, Ozgur Kisi, Ye Chow Kuang, Sajad Madadi, Mojtaba Maghrebi, Ammar Mahmood, Manish Mandloi, Mohamed Arezki Mellal, Youssef El Merabet, Subhadeep Metya, Seyedali Mirjalili, Behnam Mohammadi-Ivatloo, Ranajeet Mohanty, Abdelmalik Moujahid, Aparajita Mukherjee, V. Mukherjee, Tanmoy Mukhopadhyay, J. Mukund Nilakantan, Morteza Nazari-Heris, Peter Nielsen, Stavros Ntalampiras, Melanie Po-Leen Ooi, Ashalata Panigrahi, Manas R. Patra, S.G. Ponnambalam, Dharmbir Prasad, Yassine Ruichek, Kamna Sachdeva, Mohamed G. Sahab, Houssam Salmane, Serkan Saydam, Jalal Shiri, Ferdous Sohel, Hong Kuan Sok, Shakti Suman, Vassili V. Toropov, Carme Torras, Paraskevas Tsangaratos, Edward J. Williams, Selim Yilmaz, Milad Zamani-Gargari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ce8403040fa779de02a61a064148279
https://doi.org/10.1016/b978-0-12-811318-9.00039-9
https://doi.org/10.1016/b978-0-12-811318-9.00039-9
Alternating Decision Tree (ADTree) is a special class of classification models. It is a generalization of classical Decision Trees, Voted Decision Trees, and Voted Decision Stumps. It allows any boosting implementation as a learning mechanism to extr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e9452cbe60ba2a0b5d500e30ba00184
https://doi.org/10.1016/b978-0-12-811318-9.00019-3
https://doi.org/10.1016/b978-0-12-811318-9.00019-3
Autor:
Hong Kuan Sok, Mohammed Shahnewaz Chowdhury, Melanie Po-Leen Ooi, Ye Chow Kuang, Serge Demidenko
Publikováno v:
I2MTC
There is a chicken-and-egg problem in classification whereby a good classifier is required to test the efficacy of the features, yet a good feature set is required to generate a good classifier. When the salient features are unknown, an extremely lar