Bagging Random Trees for Estimation of Tissue Softness
نویسندگان
چکیده
We present an ensemble of classifiers that can be used to predict quality characteristics of an important process in pulp and paper industry: the tissue softness estimation. This classification problem is a difficult one since, with respect to our data set, the accuracy of all the well-known classifiers is below 68%. Contrary to that, the bagging random trees ensemble model is able to increase the accuracy up to 75%.
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