Given ordered classes, one is not only concerned to maximize the classification accuracy, but also to minimize the distances between the actual and the predicted classes. This paper offers an organized study on the various methodologies that have tried to handle this problem and presents an experimental study of these methodologies with the proposed local ordinal technique, which locally conver...

  Among various statistical and data mining discriminant analysis proposed so far for group classification, linear programming discriminant analysis has recently attracted the researchers’ interest. This study evaluates multi-group discriminant linear programming (MDLP) for classification problems against well-known methods such as neural networks and support vector machine. MDLP is less compli...

The traditional classification methods of dental local anesthesia must be modified. In this paper we proved that the vascular mechanism is leading component of spongy injection. It is necessary to take into account the high effectiveness and relative safety of spongy anesthesia, as well as versatility, ease of implementation and the growing prevalence in the world. The essence of the proposed m...

A structure composed of local linear perceptrons for approximating global class discriminants is investigated. Such local linear models may be combined in a cooperative or competitive way. In the cooperative model, a weighted sum of the outputs of the local perceptrons is computed where the weight is a function of the distance between the input and the position of the local perceptron. In the c...