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Onur Dogan, Ejder Ayçin, Zeki Atil Bulut
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In today?s business environment companies should need better understanding on customers? data. Detecting similarities and differences among customers, predicting their behaviors, proposing better options and opportunities to customers, etc. became very i...
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Mahmood Ahmad, Pawel Kaminski, Piotr Olczak, Muhammad Alam, Muhammad Junaid Iqbal, Feezan Ahmad, Sasui Sasui and Beenish Jehan Khan
Supervised machine learning and its algorithms are a developing trend in the prediction of rockfill material (RFM) mechanical properties. This study investigates supervised learning algorithms?support vector machine (SVM), random forest (RF), AdaBoost, a...
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Ashishkumar Singh,Grace W Rumantir
This paper proposes the application of clustering and classification techniques on finding groupings of retailers who use the Electronic Funds Transfer at Point Of Sale (EFTPOS) facilities of a major bank in Australia. The RFM (Recency, Frequency, Moneta...
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Peter S. Fader, Bruce G.S. Hardie, and Ka Lok Lee
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