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An Evaluation of Regression Algorithms Performance for the Chemical Process of Naphthalene Sublimation

Abstract : Different regression algorithms are applied for predicting the sublimation rate of naphthalene in various working conditions: time, temperature, trainer rate and shape of the sample. The original Large Margin Nearest Neighbor Regression (LMNNR) algorithm is applied and its performance is compared to other well-established regression algorithms, such as support vector regression, multilayer perceptron neural networks, classical k-nearest neighbor, random forest, and others. The experimental results obtained show that the LMNNR algorithm provides better results than the other regression algorithms.
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Florin Leon, Andrei-Ștefan Lupu, Sabina-Adriana Floria, Doina Logofătu, Silvia Curteanu. An Evaluation of Regression Algorithms Performance for the Chemical Process of Naphthalene Sublimation. 14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2018, Rhodes, Greece. pp.219-230, ⟨10.1007/978-3-319-92007-8_19⟩. ⟨hal-01821058⟩

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