Using Support Vector Machines to Predict the Performance of MLP Neural Networks
Ricardo B. C. Prudêncio, Silvio B. Guerra, Teresa B. Ludermir · Proceedings - Brazilian Symposium on Neural Networks/Proceedings of the ... Brazilian Symposium on Neural Networks · 2008
In this work, we investigated the use of Support Vector Machines (SVM) to predict the performance of learning algorithms based on features of the learning problems, in a kind of Meta-Learning. Experiments were performed in a case study in which SVM regressors with different kernel functions were used to predict the performance of Multi-Layer Perceptron (MLP) networks. The results obtained on a set of 50 learning problems revealed that the SVMs obtained better results in predicting the MLP performance,when compared to benchmark algorithms applied in previous work.