in this paper the problem of 3d scene and object classification from depth data is addressed. in contrast to high-dimensional feature-based representation, the depth data is described in a low dimensional space. in order to remedy the curse of dimensionality problem, the depth data is described by a sparse model over a learned dictionary. exploiting the algorithmic information theory, a new def...

in this paper, first, an initial feature vector for vocal fold pathology diagnosis is proposed. then, for optimizing the initial feature vector, a genetic algorithm is proposed. some experiments are carried out for evaluating and comparing the classification accuracies which are obtained by the use of the different classifiers (ensemble of decision tree, discriminant analysis and k-nearest neig...

classifying customers using data mining algorithms, enables banks to keep old customers loyality while attracting new ones. using decision tree as a data mining technique, we can optimize customer classification provided that the appropriate decision tree is selected. in this article we have presented an appropriate model to classify customers who use internet banking service. the model is deve...