Advances in credit scoring: combining performance and interpretation in kernel discriminant analysis

DOI10.1007/s11634-015-0213-yzbMath1414.62421OpenAlexW753132656WikidataQ57599357 ScholiaQ57599357MaRDI QIDQ2418293

Furio Camillo, Caterina Liberati, Gilbert Saporta

Publication date: 3 June 2019

Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11634-015-0213-y

zbMATH Keywords

credit scoringsmall and medium enterpriseskernel discriminant analysisdisqual

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items (2)

Categorical multiblock linear discriminant analysis ⋮ Ensemble of optimal trees, random forest and random projection ensemble classification

Cites Work

• Evaluation of neural networks and data mining methods on a credit assessment task for class imbalance problem
• Support vector machines for default prediction of SMEs based on technology credit
• Efficient leave-one-out cross-validation of kernel Fisher discriminant classifiers.
• Bayesian kernel based classification for financial distress detection
• On the Choice of the Kernel Function in Kernel Discriminant Analysis Using Information Complexity
• Chaos control using least-squares support vector machines
• Benchmarking state-of-the-art classification algorithms for credit scoring
• Choosing multiple parameters for support vector machines
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