Search Results - subject:"Support Vector Machine"

Forecasting demand with support vector regression technique incorporating feature selection in the presence of calendar effect

Sarhani, Malek; El Afia, Abdellatif - In: Contemporary approaches and strategies for applied logistics, (pp. 302-316). 2018

Persistent link: https://www.econbiz.de/10011859422

Making Better Decisions Using Systems Thinking : How to stop firefighting, deal with root causes and deliver permanent solutions

Schaveling, Jaap; Bryan, Bill - 2018

This book shows how to understand systems in order to make smarter decisions. It offers managers intervention techniques that enable them to solve the core problem instead of wasting time constantly fighting the symptoms. The most obvious part of any problem is the pain it causes. The desire to...

Persistent link: https://www.econbiz.de/10012396663

Chinese bank efficiency during the global financial crisis : a combined approach using satisficing DEA and Support Vector Machines

Chen, Zhongfei; Matousek, Roman; Wanke, Peter - In: The North American journal of economics and finance : a … 43 (2018), pp. 71-86

Persistent link: https://www.econbiz.de/10012036260

Angle-based twin support vector machine

Khemchandani, Reshma; Saigal, Pooja; Chandra, Suresh - In: Recent advances in optimization theory and applications, (pp. 387-417). 2018

Persistent link: https://www.econbiz.de/10011943549

Predicting bank failure : an improvement by implementing a machine-learning approach to classical financial ratios

Le, Hong Hanh; Viviani, Jean-Laurent - In: Research in international business and finance 44 (2018), pp. 16-25

Persistent link: https://www.econbiz.de/10011982957

Small sample-oriented case-based kernel predictive modeling and its economic forecasting applications under n-splits-k-times hold-out assessment

Li, Hui; Hong, Lu-yao; He, Jia-xun; Xu, Xuan-guo; Sun, Jie - In: Economic modelling 33 (2013), pp. 747-761

Persistent link: https://www.econbiz.de/10010194401

Product service system configuration based on support vector machine considering customer perception

Long, H. J.; Wang, L. Y.; Shen, J.; Wu, M. X.; Jiang, Z. B. - In: International journal of production research 51 (2013) 18, pp. 5450-5468

Persistent link: https://www.econbiz.de/10010196566

Forecasting the insolvency of US banks using Support Vector Machines (SVMs) based on local learning feature selection

Papadimitriou, Theophilos; Gkonkas, Periklēs; … - In: International journal of computational economics and … 3 (2013) 1/2, pp. 83-90

Persistent link: https://www.econbiz.de/10010250320

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

Support vector machines with evolutionary feature selection for default prediction

Härdle, Wolfgang Karl; Prastyo, Dedy Dwi; Hafner, Christian - 2012

Predicting default probabilities is at the core of credit risk management and is becoming more and more important for banks in order to measure their client's degree of risk, and for firms to operate successfully. The SVM with evolutionary feature selection is applied to the CreditReform...

Persistent link: https://www.econbiz.de/10010318756