Qualitative company performance evaluation: Linear discriminant analysis and neural network models

An efficient classifier to diagnose of schizophrenia based on the EEG signals

“…It can be seen that BDLDA is also more robust than the two other classifiers. The reason is that BDLDA benefit from robustness of LDA (Bertels, Jacques, Neuberg, & Gatot, 1999) and generalization property of Adaboost scheme (Murua, 2002). Moreover, regarding the high dimensionality of the feature vectors (286), BDLDA uses Direct LDA as its weak learner which reduces the dimension of input vectors while it increases the discrimination of the transformed feature vectors (Gao & Davis, 2006).…”

Analyzing customer satisfaction and service level using AI technique

“…Furthermore, they provide insights into the structural characteristics of neural networks with respect to the input data used as well as possible mechanisms to improve the learning performance. Bertel and Mneuberg(1999) presented a classification model to evaluate the performance of companies on the basis of qualitative criteria, such as organizational and managerial variables. They created a similar model using the back-propagation learning algorithm and compare its classification performance against the linear model.…”

Forecasting business profitability by using classification techniques: A comparative analysis based on a Spanish case

“…Rule induction systems outperform Logit and LDA in the training sample, but the efficiency of induction systems drops substantially in the validation sample Varetto (1998) Insolvency prediction • LDA • Genetic algorithms LDA proved to be slightly better than linear classifiers generated through genetic algorithms and the calculation of scores based on rules obtained using genetic algorithms Bertels et al (1999) Evaluate the eligibility of a company to receive state subsidies…”