Ensembles of Locally Linear Models: Application to Bankruptcy Prediction
نویسندگان
چکیده
The bankruptcies of companies have been predicted with numerous methods. In this paper, the ensemble of Locally Linear model is compared to Linear Discriminant Analysis, Least Squares Support Vector Machines and Optimally Pruned Extreme Learning Machines. To create the ensemble, diffrerent basis for the locally linear models as well as different combinations of variables are used in order to obtain enough diversity between the models. The obtained models are combined into the final model by solving a least-squares nonnegative constraints problem. The model is tested on a Polish bankruptcy data set and the results discussed also from the point of view of importance of the variables.
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Ensembles of Local Linear Models for Bankruptcy Analysis and Prediction
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