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The Big Data revolution promises to transform how we live, work, and think by enabling process optimization, empowering insight discovery and improving decision making. The realization of this grand potential relies on the ability to extract value from such massive data through data analytics; machine learning is at its core because of its ability to learn from data and provide data driven insights,...
We review the fact that several kinds of neural networks can be trained to approximate other types of discriminant functions, thereby throwing some doubt upon the utility of the No Free Lunch theorem. Using a license plate recognition database with 36 classes, we then demonstrate that multilayer perceptrons estimate posterior probabilities very poorly when the number of classes is large. A method...
In this paper, we propose an evolutionary approach to the design of output codes for multiclass pattern recognition problems. This approach has the advantage of taking into account the different aspects that are relevant for a code matrix to achieve a good performance. We define a fitness function made up of five terms that refer to overall classifier accuracy, binary classifiers' accuracy, classifiers'...
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