The diploma thesis covers the field of machine learning. In more detail it covers the field of deep neural networks. The goal of our thesis was comparing different approaches of machine learning for building models for automated essay scoring and to evaluate the success of deep neural networks compared to other models. For building models we have used already extracted attributes, but for the deep neural network we have also used original essays, represented by the three attributes, that represent the relationships in a sentence. For comparing we have used the R environment, where we have built, tested and compared the models. Many different models of the same kind were built, from which the best was chosen for further comparison with models of different types.
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