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Associative classification apporaches : review and comparison
Abdelhamid, Neda; Thabtah, Fadi - In: Journal of information & knowledge management : JIKM 13 (2014) 3, pp. 1-30
Persistent link: https://www.econbiz.de/10010438960
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ACRIPPER : a new associative classification based on RIPPER algorithm
Abu-Arqoub, Mohammed; Hadi, Wa'el; Ishtaiwi, Abdelraouf - In: Journal of information & knowledge management : JIKM 20 (2021) 1, pp. 2150013-1-2150013-21
Persistent link: https://www.econbiz.de/10012602460
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A new associative classification algorithm for predicting groundwater locations
Aburub, Faisal; Hadi, Wa’el - In: Journal of information & knowledge management : JIKM 17 (2018) 4, pp. 1850043-1-26
Persistent link: https://www.econbiz.de/10011990817
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Metaheuristics for data mining : survey opportunities for big data
Dhaenens, Clarisse; Jourdan, Laetitia - In: 4OR : a quarterly journal of operations research 17 (2019) 2, pp. 115-139
Persistent link: https://www.econbiz.de/10012007902
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An efficient FLANN model with CRO-based gradient descent learning for classification
Naik, Bighnaraj; Nayak, Janmenjoy; Behera, Himansu Sekhar - In: International journal of business information systems : … 21 (2016) 1, pp. 73-116
Persistent link: https://www.econbiz.de/10011520250
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Classification of the main financial-banking institutions in Romania using SAS
Mihaela, Iordache Ana Maria; Octavian, Mihalcescu Cezar; … - In: Romanian economic and business review 15 (2020) 4, pp. 25-34
Persistent link: https://www.econbiz.de/10012631921
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A multi-label machine learning approach to support pathologist's histological analysis
Azzini, Antonia; Cortesi, Nicola; Marrara, Stefania; … - In: Proceedings of the ENTRENOVA - ENTerprise REsearch … 5 (2019) 1, pp. 197-208
, if properly extracted, may be suitable for searching, classification, or statistical analysis. For this reason, in order … work presents a Machine Learning Multi-Label approach for the classification of the information extracted from the …
Persistent link: https://www.econbiz.de/10012221872
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Modelling and predicting student's academic performance using classification data mining techniques
Raza Hasan; Sellappan Palaniappan; Salman Mahmood; … - In: International journal of business information systems : … 34 (2020) 3, pp. 403-422
Persistent link: https://www.econbiz.de/10012253494
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Features selection, data mining and finacial risk classification : a comparative study
Lahmiri, Salim - In: Intelligent systems in accounting finance and … 23 (2016) 4, pp. 265-275
Persistent link: https://www.econbiz.de/10011668094
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Data mining approach for predicting student performance
Osmanbegović, Edin; Suljić, Mirza - In: Economic review : journal of economics & business 10 (2012) 1, pp. 3-12
Although data mining has been successfully implemented in the business world for some time now, its use in higher education is still relatively new, i.e. its use is intended for identification and extraction of new and potentially valuable knowledge from the data. Using data mining the aim was...
Persistent link: https://www.econbiz.de/10012010545