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Research on Machine Learning and Neural Network techniques applied to the classification of encephalographic signals regarding concept evocation and movement intention
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‎BCI - Paper [ES].pdf‎

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‎Code/Models/RandomForest1-metrics.txt‎

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‎Code/Models/RandomForest2-metrics.txt‎

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‎Code/Models/RecurrentNN1-metrics.txt‎

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RRN LSTM: EVOCACI�N DE CONCEPTO
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Promedio Global de M�tricas
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* Accuracy: 0.7477
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* Recall Macro: 0.7629
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* F1 Macro: 0.7389
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* Precision:
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* Clase "�rbol": 0.9526
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* Clase "Cuaderno": 0.5809
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* Clase "Computadora": 0.9499
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* Clase "Perro": 0.5628

‎Code/Models/RecurrentNN2-metrics.txt‎

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RRN LSTM: INTENCI�N DE MOVIMIENTO
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Promedio Global de M�tricas
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* Accuracy: 0.7419
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* Recall Macro: 0.7548
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* F1 Macro: 0.7320
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* Precision:
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* Clase "MouseUp": 0.9205
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* Clase "MouseDown": 0.5648
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* Clase "MouseLeft": 0.9159
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* Clase "MouseRight": 0.5832
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