Update README.md

tobiasfshr · Aug 22, 2018 · 53a2865 · 53a2865
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@@ -18,7 +18,7 @@ The train/validation/test split is 80% / 5% / 15%. Together with the data augmen
 
 Results
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-As classification models I evaluated Recurrent Neural Networks (RNN) with Gated Recurrent Units (GRU), Convolutional Neural Networks and other, more classical machine learning models like Hidden Markov Models (HMM), Random Forests, Multi-Layer Perceptrons (MLP) and Support Vector Machines (SVM). However, the classical models did not provide a satisfying accuracy.
+As classification models I evaluated Recurrent Neural Networks (RNN) with Gated Recurrent Units (GRU), Convolutional Neural Networks (CNN) and other, more classical machine learning models like Hidden Markov Models (HMM), Random Forests, Multi-Layer Perceptrons (MLP) and Support Vector Machines (SVM). However, the classical models did not provide a satisfying accuracy.
 
 Model | Accuracy
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