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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

Interpretable support vector machines for functional data

Martin-Barragan, Belen; Lillo, Rosa; Romo, Juan - In: European journal of operational research : EJOR 232 (2014) 1, pp. 146-155

Persistent link: https://www.econbiz.de/10010224722

Application of predictive methods to financial data sets

Habibi, Reza - In: Financial internet quarterly 17 (2021) 1, pp. 50-61

Financial data sets are growing too fast and need to be analyzed. Data science has many different techniques to store and summarize, mining, running simulations and finally analyzing them. Among data science methods, predictive methods play a critical role in analyzing financial data sets. In...

Persistent link: https://www.econbiz.de/10012588934

A modified Bayesian boosting algorithm with weight-guided optimal feature selection for sentiment analysis

Nayak, Smitha; Savita; Sharma, Yogesh Kumar - In: Decision analytics journal 8 (2023), pp. 1-13

. The goal is to improve the accuracy and efficiency of sentiment classification by selecting the most informative features … that assigns weights to individual features based on their importance in sentiment classification. This weight …-guided feature selection approach helps identify the most relevant and discriminative features, enhancing classification performance …

Persistent link: https://www.econbiz.de/10014517151

Machine learning approaches for early DRG classification and resource allocation

Gartner, Daniel; Kolisch, Rainer; Neill, Daniel B.; … - In: INFORMS journal on computing : JOC 27 (2015) 4, pp. 718-734

Persistent link: https://www.econbiz.de/10011422689

A classifier to decide on the linearization of mixed-integer quadratic problems in CPLEX

Bonami, Pierre; Lodi, Andrea; Zarpellon, Giulia - In: Operations research 70 (2022) 6, pp. 3303-3320

Persistent link: https://www.econbiz.de/10014307820

On multivariate randomized classification trees l0- based sparsity, VC dimension and decomposition methods

Amaldi, Edoardo; Consolo, Antonio; Manno, Andrea - In: Computers & operations research : and their … 151 (2023), pp. 1-21

Persistent link: https://www.econbiz.de/10014234818

Support vector machines maximizing geometric margins for multi-class classification

Tatsumi, Keiji; Tanino, Tetsuzo - In: Top : transactions in operations research 22 (2014) 3, pp. 815-840

Persistent link: https://www.econbiz.de/10010437131

Column generation based heuristic for learning classification trees

Firat, Murat; Crognier, Guillaume; Gabor, Adriana F.; … - In: Computers & operations research : and their … 116 (2020), pp. 1-11

Persistent link: https://www.econbiz.de/10012164803

Margin optimal classification trees

D'Onofrio, Federico; Grani, Giorgio; Monaci, Marta; … - In: Computers & operations research : an international journal 161 (2024), pp. 1-19

Persistent link: https://www.econbiz.de/10014559221