Kalman filter is, in certain sense, a way to give the moving average of a time series. It keeps track on a vector of state variables with its corresponding covariance matrix. The Kalman algorithm usually give a converging covariance matrix after several iterations of prediction-update. A common use is to...
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Shi and Xu (2016) Credit Scoring by Fuzzy Support Vector Machines with a Novel Membership Function
The paper by Wang et al (2005) introduced the fuzzy
SVM but did not address how we can obtain the membership value. This paper fill
up the void.
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Wang, Wang, & Lai (2005) A New Fuzzy Support Vector Machine to Evaluate Credit Risk
A paper referenced by Yu (2014) which introduced the
FSVM to the domain.
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Yu (2014) Credit Risk Evaluation with a Least Squares Fuzzy Support Vector Machine Classifier
A paper first surveys some variations of support vector machines and their solution, and then apply to credit risk evaluation.
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Suykens and Vandewalle (1999) Least Squares Support Vector Machine Classifiers
A short paper reviews the prior work on SVM with kernel functions and then move
on the introduce a SVM classifier formulated by optimizing for least square
error. Refer to previous post for notations.
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