Alreshidi, IbrahimMoulitsas, IreneJenkins, KarlYadav, Satendra2024-06-032024-06-032023-09-18Alreshidi, Ibrahim; Moulitsas, Irene; Jenkins, Karl; Yadav, Satendra (2023). Code and data supporting 'A Comprehensive Analysis of Machine Learning and Deep Learning Models for Identifying Pilots' Mental States from Imbalanced Physiological Data'. Cranfield Online Research Data (CORD). Software. https://doi.org/10.17862/cranfield.rd.24156345https://dspace.lib.cranfield.ac.uk/handle/1826/21793Data: This folder contains: - A dataset called combined_df4, which contains the power spectral density features after employing SMOTE. - A dataset called combined_df5, which contains the power spectral density features after employing SMOTE and cosine similarity. Source code: This folder contains: - A jupyter notebook called AdaBoost.ipynb which was used to generate the results for the AdaBoost algorithm. - A jupyter notebook called CNN.ipynb which was used to generate the results for the CNN algorithm. - A jupyter notebook called CNN+LSTM.ipynb which was used to generate the results for the CNN+LSTMalgorithm. - A jupyter notebook called LSTM.ipynb which was used to generate the results for the LSTMalgorithm. - A jupyter notebook called FNN.ipynb which was used to generate the results for the FNN algorithm. - A jupyter notebook called Random_Forest.ipynb which was used to generate the results for the Random Forest algorithm. - A jupyter notebook called XGBoost.ipynb which was used to generate the results for the XGBoost algorithm.MITMachine Learning''Pilot Deficiencies''Mental State Classifications'Software10.17862/cranfield.rd.24156345