Philippe du Jardin

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We evaluate the prediction accuracy of models designed using different classification methods depending on the technique used to select variables, and we study the relationship between the structure of the models and their ability to correctly predict financial failure. We show that a neural network based model using a set of variables selected with a(More)
The measurement of the femoral head is usually considered an interesting variable for the sex determination of skeletal remains. To date, there are few published reference measurements of the femoral head in a modern European population for the purpose of sex determination. In this study, 116 femurs from 58 individuals of the South of France (Nice Bone(More)
This experimental study examined the lesions produced by a hatchet on human bones (tibiae). A total of 30 lesions were produced and examined macroscopically (naked eye) and by stereomicroscopy. 13 of them were also analyzed using scanning electron microscopy. The general shape of the lesion, both edges, both walls, the kerf floor and the extremities were(More)
This study attempts to show how a Kohonen map can be used to improve the temporal stability of the accuracy of a financial failure model. Most models lose a significant part of their ability to generalize when data used for estimation and prediction purposes are collected over different time periods. As their lifespan is fairly short, it becomes a real(More)
Various methods have been published in the literature to estimate endocranial capacity. These are based on mathematical equations using measurements made directly on the skull or indirectly from X-rays, by filling the skull with various materials, by endocasts both physical and virtual (using 3D CT-scan reconstructions). Each method has its advantages,(More)
Traditional bankruptcy prediction models, designed using classification or regression techniques, achieve short-term performances (1 year) that are fairly good, but that often worsen when the prediction horizon exceeds 1 year. We show how to improve the performance of such models beyond one year using models that take into account the evolution of firm(More)
Of the methods used to build bankruptcy prediction models in the last twenty years, neural networks are among the most challenging. Despite the characteristics of neural networks, most of the research done until now has not taken them into consideration for building financial failure models, nor for selecting the variables to be included in the models. The(More)