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  1. C:\ProgramData\Anaconda3\python.exe C:/Users/mohe01/EventServerAnalyzer/Source/KOALAELearningAnalyzer.py
  2. =================================== QUIZZES ===================================
  3.  
  4. Analyzing Feature Selection + classification models for obj. Difficulty
  5. SGDClassifier L2
  6. Performing Feature Selection based on: video_difficulty
  7. Overall there are 240 features. Reducing these now!
  8. Best 30 of 240 Features: ['CDA_AmpSum', 'CDA_ISCR', 'CDA_PhasicMax', 'CDA_SCR', 'TTP_nSCR', 'acc_dist_to_head', 'acc_empatica_gsr', 'acc_polar_nn50', 'acc_raw_pupil', 'avg_garmin_sdnn', 'fix_amount', 'freq_frame16_acc_empatica_gsr', 'freq_frame16_max_empatica_gsr', 'freq_frame32_acc_empatica_gsr', 'freq_frame32_max_empatica_gsr', 'max_ear', 'max_empatica_bvp_amplitude', 'max_empatica_gsr', 'max_msband_gsr', 'min_msband_gsr', 'min_polar_hr', 'min_polar_rr', 'range_empatica_rmssd', 'range_msband_gsr', 'range_raw_pupil', 'std_empatica_bvp_median_abs_dev', 'std_empatica_sdnn', 'std_garmin_rmssd', 'std_hilbert', 'std_ica_interpolated_stat']
  9. Training a SGDClassifier CV classification model for obj. difficulty
  10. Features: {'Skin': 14, 'Body Posture': 1, 'Heart': 9, 'Eye': 6}
  11. Avg CV Score: 0.77976
  12. -------------
  13. LogisticRegression L1
  14. Performing Feature Selection based on: video_difficulty
  15. Overall there are 240 features. Reducing these now!
  16. Best 30 of 240 Features: ['CDA_PhasicMax', 'CDA_SCR', 'Global_MaxDeflection', 'Global_Mean', 'TTP_nSCR', 'acc_ica_interpolated', 'acc_ica_interpolated_stat', 'acc_polar_pnn50', 'acc_raw_pupil', 'avg_hilbert', 'avg_ica_interpolated_stat', 'avg_raw_pupil', 'fix_amount', 'freq_frame16_acc_empatica_gsr', 'freq_frame16_max_empatica_gsr', 'max_ear', 'max_empatica_bvp_amplitude', 'max_garmin_hr', 'max_garmin_pnn50', 'min_garmin_rmssd', 'min_msband_gsr', 'min_polar_hr', 'range_dist_to_head', 'range_empatica_rmssd', 'range_raw_pupil', 'std_empatica_ibi', 'std_empatica_sdnn', 'std_hilbert', 'std_ica_interpolated_stat', 'std_msband_gsr']
  17. Training a LogisticRegression CV classification model for obj. difficulty
  18. Features: {'Skin': 9, 'Eye': 11, 'Heart': 9, 'Body Posture': 1}
  19. Avg CV Score: 0.8011900000000001
  20. -------------
  21. LogisticRegression L2
  22. Performing Feature Selection based on: video_difficulty
  23. Overall there are 240 features. Reducing these now!
  24. Best 30 of 240 Features: ['CDA_PhasicMax', 'CDA_SCR', 'CDA_Tonic', 'Global_MaxDeflection', 'Global_Mean', 'TTP_nSCR', 'acc_dist_to_head', 'acc_ica_interpolated_stat', 'acc_polar_nn50', 'acc_raw_pupil', 'avg_garmin_sdnn', 'avg_hilbert', 'avg_ica_interpolated_stat', 'avg_raw_pupil', 'fix_amount', 'freq_frame16_acc_empatica_gsr', 'max_empatica_ibi', 'max_garmin_hr', 'max_garmin_nn50', 'min_garmin_rmssd', 'min_hilbert', 'min_msband_gsr', 'min_polar_hr', 'range_empatica_rmssd', 'range_raw_pupil', 'std_empatica_sdnn', 'std_garmin_rmssd', 'std_hilbert', 'std_ica_interpolated_stat', 'std_msband_gsr']
  25. Training a LogisticRegression CV classification model for obj. difficulty
  26. Features: {'Skin': 9, 'Body Posture': 1, 'Eye': 10, 'Heart': 10}
  27. Avg CV Score: 0.84881
  28. -------------
  29. RandomForestClassifier
  30. Performing Feature Selection based on: video_difficulty
  31. Overall there are 240 features. Reducing these now!
  32. Best 30 of 240 Features: ['acc_raw_pupil', 'acc_sacc_duration', 'acc_search_prob', 'avg_ear', 'avg_empatica_bvp', 'avg_empatica_bvp_mean_abs_diff', 'avg_empatica_gsr', 'avg_empatica_ibi', 'avg_empatica_rmssd', 'avg_empatica_sdnn', 'avg_empatica_temp', 'avg_fix_duration', 'avg_garmin_hr', 'avg_garmin_nn50', 'avg_polar_pnn50', 'blink_amount', 'fix_amount', 'freq_frame32_avg_empatica_gsr', 'freq_frame64_acc_empatica_gsr', 'min_garmin_ibi', 'min_polar_rr', 'range_empatica_bvp_mean_abs_diff', 'range_empatica_ibi', 'range_empatica_rmssd', 'range_ica_interpolated', 'range_msband_gsr', 'range_raw_pupil', 'std_empatica_bvp_mean_abs_diff', 'std_empatica_bvp_median_abs_dev', 'std_empatica_ibi']
  33. Training a RandomForestClassifier CV classification model for obj. difficulty
  34. Features: {'Eye': 9, 'Heart': 16, 'Skin': 5}
  35. Avg CV Score: 0.76429
  36. -------------
  37.  
  38. Analyzing Feature Selection + regression models for subj. Difficulty Rating
  39. SGDRegressor
  40. Performing Feature Selection based on: difficulty_rating
  41. Overall there are 240 features. Reducing these now!
  42. Best 30 of 240 Features: ['CDA_ISCR', 'CDA_Tonic', 'Global_Mean', 'acc_dist_to_head', 'acc_empatica_gsr', 'acc_garmin_nn50', 'acc_garmin_pnn50', 'acc_ica_interpolated_stat', 'acc_raw_pupil', 'avg_empatica_ibi', 'avg_garmin_rmssd', 'avg_ica_interpolated_stat', 'avg_polar_hr', 'avg_polar_pnn50', 'blink_amount', 'freq_frame16_max_empatica_gsr', 'freq_frame32_max_empatica_gsr', 'freq_frame64_max_empatica_gsr', 'max_fix_duration', 'max_ica_interpolated_stat', 'max_msband_gsr', 'min_ear', 'min_garmin_rmssd', 'min_polar_rr', 'min_search_prob', 'norm_blink_amount', 'range_msband_gsr', 'std_empatica_ibi', 'std_garmin_hr', 'std_msband_gsr']
  43. Training a SGDRegressor CV regression model for subj. Difficulty Rating
  44. Features: {'Skin': 10, 'Body Posture': 1, 'Heart': 10, 'Eye': 9}
  45. Avg CV Score: -1.95317
  46. -------------
  47. Lasso
  48. Performing Feature Selection based on: difficulty_rating
  49. Overall there are 240 features. Reducing these now!
  50. Best 30 of 240 Features: ['std_empatica_bvp_mean_abs_diff', 'std_empatica_bvp_median_abs_dev', 'std_empatica_gsr', 'std_empatica_ibi', 'std_empatica_nn50', 'std_empatica_pnn50', 'std_empatica_rmssd', 'std_empatica_sdnn', 'std_empatica_temp', 'std_fix_duration', 'std_garmin_hr', 'std_garmin_ibi', 'std_garmin_nn50', 'std_garmin_pnn50', 'std_garmin_rmssd', 'std_garmin_sdnn', 'std_garmin_temp', 'std_hilbert', 'std_ica_interpolated', 'std_ica_interpolated_stat', 'std_msband_gsr', 'std_polar_hr', 'std_polar_nn50', 'std_polar_pnn50', 'std_polar_rmssd', 'std_polar_rr', 'std_polar_sdnn', 'std_raw_pupil', 'std_sacc_duration', 'std_search_prob']
  51. Training a Lasso CV regression model for subj. Difficulty Rating
  52. Features: {'Heart': 19, 'Skin': 4, 'Eye': 7}
  53. Avg CV Score: -1.5988599999999997
  54. -------------
  55. ElasticNet
  56. Performing Feature Selection based on: difficulty_rating
  57. Overall there are 240 features. Reducing these now!
  58. Best 30 of 240 Features: ['acc_dist_to_head', 'acc_ear', 'acc_empatica_bvp', 'acc_empatica_bvp_amplitude', 'acc_empatica_bvp_mean_abs_diff', 'acc_empatica_bvp_median_abs_dev', 'acc_empatica_gsr', 'acc_empatica_ibi', 'acc_empatica_nn50', 'acc_empatica_pnn50', 'acc_empatica_rmssd', 'acc_empatica_sdnn', 'acc_empatica_temp', 'acc_fix_duration', 'acc_garmin_hr', 'acc_ica_interpolated_stat', 'acc_raw_pupil', 'std_empatica_bvp', 'std_empatica_bvp_amplitude', 'std_empatica_bvp_mean_abs_diff', 'std_empatica_bvp_median_abs_dev', 'std_empatica_gsr', 'std_empatica_ibi', 'std_empatica_nn50', 'std_empatica_pnn50', 'std_empatica_rmssd', 'std_empatica_sdnn', 'std_empatica_temp', 'std_fix_duration', 'std_garmin_hr']
  59. Training a ElasticNet CV regression model for subj. Difficulty Rating
  60. Features: {'Body Posture': 1, 'Eye': 5, 'Heart': 20, 'Skin': 4}
  61. Avg CV Score: -1.3414199999999998
  62. -------------
  63. RandomForestRegressor
  64. Performing Feature Selection based on: difficulty_rating
  65. Overall there are 240 features. Reducing these now!
  66. Best 30 of 240 Features: ['CDA_PhasicMax', 'Global_Mean', 'acc_dist_to_head', 'acc_empatica_bvp_amplitude', 'acc_empatica_rmssd', 'acc_empatica_temp', 'acc_garmin_ibi', 'acc_garmin_rmssd', 'acc_ica_interpolated', 'acc_raw_pupil', 'avg_empatica_bvp_amplitude', 'avg_fix_duration', 'avg_garmin_pnn50', 'blink_amount', 'freq_frame16_max_empatica_gsr', 'freq_frame32_range_empatica_gsr', 'max_empatica_temp', 'max_raw_pupil', 'max_sacc_duration', 'min_empatica_gsr', 'min_raw_pupil', 'range_empatica_bvp_amplitude', 'range_empatica_bvp_median_abs_dev', 'range_ica_interpolated_stat', 'range_msband_gsr', 'range_raw_pupil', 'std_empatica_bvp', 'std_empatica_rmssd', 'std_msband_gsr', 'std_raw_pupil']
  67. Training a RandomForestRegressor CV regression model for subj. Difficulty Rating
  68. Features: {'Skin': 9, 'Body Posture': 1, 'Heart': 10, 'Eye': 10}
  69. Avg CV Score: -1.13856
  70. -------------
  71. Ridge
  72. Performing Feature Selection based on: difficulty_rating
  73. Overall there are 240 features. Reducing these now!
  74. Best 30 of 240 Features: ['CDA_ISCR', 'acc_dist_to_head', 'acc_empatica_ibi', 'acc_garmin_nn50', 'acc_garmin_pnn50', 'acc_polar_hr', 'acc_sacc_duration', 'avg_empatica_gsr', 'avg_ica_interpolated_stat', 'avg_polar_hr', 'avg_polar_nn50', 'avg_polar_pnn50', 'avg_polar_sdnn', 'freq_avg_empatica_gsr', 'max_empatica_bvp', 'max_empatica_bvp_amplitude', 'max_empatica_gsr', 'max_msband_gsr', 'max_polar_sdnn', 'min_ear', 'min_garmin_nn50', 'min_garmin_rmssd', 'norm_blink_amount', 'range_empatica_bvp_amplitude', 'range_polar_pnn50', 'range_raw_pupil', 'std_empatica_bvp_amplitude', 'std_ica_interpolated_stat', 'std_polar_rr', 'std_raw_pupil']
  75. Training a Ridge CV regression model for subj. Difficulty Rating
  76. Features: {'Skin': 5, 'Body Posture': 1, 'Heart': 17, 'Eye': 7}
  77. Avg CV Score: -0.7360800000000001
  78. -------------
  79.  
  80. Analyzing Feature Selection + regression models for subj. CL Rating
  81. SGDRegressor
  82. Performing Feature Selection based on: cl_rating
  83. Overall there are 240 features. Reducing these now!
  84. Best 30 of 240 Features: ['acc_dist_to_head', 'acc_empatica_gsr', 'acc_empatica_temp', 'acc_ica_interpolated_stat', 'acc_raw_pupil', 'avg_empatica_ibi', 'avg_garmin_nn50', 'avg_garmin_pnn50', 'avg_ica_interpolated_stat', 'avg_polar_hr', 'avg_polar_rr', 'blink_amount', 'freq_frame16_max_empatica_gsr', 'freq_frame32_max_empatica_gsr', 'max_ear', 'max_empatica_bvp', 'max_msband_gsr', 'max_polar_nn50', 'min_ear', 'min_garmin_rmssd', 'min_garmin_sdnn', 'min_sacc_duration', 'min_search_prob', 'norm_fix_amount', 'range_garmin_rmssd', 'range_msband_gsr', 'std_garmin_hr', 'std_msband_gsr', 'std_polar_rr', 'std_raw_pupil']
  85. Training a SGDRegressor CV regression model for subj. CL Rating ...
  86. Features: {'Body Posture': 1, 'Skin': 7, 'Eye': 10, 'Heart': 12}
  87. Avg CV Score: -3.2556199999999995
  88. -------------
  89. Lasso
  90. Performing Feature Selection based on: cl_rating
  91. Overall there are 240 features. Reducing these now!
  92. Best 30 of 240 Features: ['std_empatica_bvp_mean_abs_diff', 'std_empatica_bvp_median_abs_dev', 'std_empatica_gsr', 'std_empatica_ibi', 'std_empatica_nn50', 'std_empatica_pnn50', 'std_empatica_rmssd', 'std_empatica_sdnn', 'std_empatica_temp', 'std_fix_duration', 'std_garmin_hr', 'std_garmin_ibi', 'std_garmin_nn50', 'std_garmin_pnn50', 'std_garmin_rmssd', 'std_garmin_sdnn', 'std_garmin_temp', 'std_hilbert', 'std_ica_interpolated', 'std_ica_interpolated_stat', 'std_msband_gsr', 'std_polar_hr', 'std_polar_nn50', 'std_polar_pnn50', 'std_polar_rmssd', 'std_polar_rr', 'std_polar_sdnn', 'std_raw_pupil', 'std_sacc_duration', 'std_search_prob']
  93. Training a Lasso CV regression model for subj. CL Rating ...
  94. Features: {'Heart': 19, 'Skin': 4, 'Eye': 7}
  95. Avg CV Score: -2.6206899999999997
  96. -------------
  97. ElasticNet
  98. Performing Feature Selection based on: cl_rating
  99. Overall there are 240 features. Reducing these now!
  100. Best 30 of 240 Features: ['acc_dist_to_head', 'acc_ear', 'acc_empatica_bvp', 'acc_empatica_bvp_amplitude', 'acc_empatica_bvp_mean_abs_diff', 'acc_empatica_bvp_median_abs_dev', 'acc_empatica_gsr', 'acc_empatica_ibi', 'acc_empatica_nn50', 'acc_empatica_pnn50', 'acc_empatica_rmssd', 'acc_empatica_sdnn', 'acc_empatica_temp', 'acc_fix_duration', 'acc_garmin_hr', 'acc_ica_interpolated_stat', 'acc_raw_pupil', 'std_empatica_bvp', 'std_empatica_bvp_amplitude', 'std_empatica_bvp_mean_abs_diff', 'std_empatica_bvp_median_abs_dev', 'std_empatica_gsr', 'std_empatica_ibi', 'std_empatica_nn50', 'std_empatica_pnn50', 'std_empatica_rmssd', 'std_empatica_sdnn', 'std_empatica_temp', 'std_fix_duration', 'std_garmin_hr']
  101. Training a ElasticNet CV regression model for subj. CL Rating ...
  102. Features: {'Body Posture': 1, 'Eye': 5, 'Heart': 20, 'Skin': 4}
  103. Avg CV Score: -2.1563899999999996
  104. -------------
  105. RandomForestRegressor
  106. Performing Feature Selection based on: cl_rating
  107. Overall there are 240 features. Reducing these now!
  108. Best 30 of 240 Features: ['CDA_ISCR', 'acc_dist_to_head', 'acc_empatica_bvp', 'acc_empatica_bvp_amplitude', 'acc_ica_interpolated', 'acc_ica_interpolated_stat', 'acc_msband_gsr', 'acc_polar_hr', 'acc_raw_pupil', 'acc_sacc_duration', 'avg_empatica_bvp_mean_abs_diff', 'avg_empatica_ibi', 'avg_search_prob', 'blink_amount', 'freq_frame32_acc_empatica_gsr', 'freq_frame32_max_empatica_gsr', 'freq_frame64_avg_empatica_gsr', 'max_ear', 'max_hilbert', 'max_msband_gsr', 'max_polar_nn50', 'max_polar_rr', 'min_dist_to_head', 'min_empatica_bvp', 'min_empatica_gsr', 'min_garmin_rmssd', 'range_empatica_ibi', 'range_empatica_nn50', 'std_empatica_ibi', 'std_garmin_sdnn']
  109. Training a RandomForestRegressor CV regression model for subj. CL Rating ...
  110. Features: {'Skin': 7, 'Body Posture': 2, 'Heart': 13, 'Eye': 8}
  111. Avg CV Score: -1.8497
  112. -------------
  113. Ridge
  114. Performing Feature Selection based on: cl_rating
  115. Overall there are 240 features. Reducing these now!
  116. Best 30 of 240 Features: ['acc_dist_to_head', 'acc_ica_interpolated_stat', 'acc_polar_hr', 'avg_empatica_bvp_amplitude', 'avg_garmin_rmssd', 'avg_ica_interpolated_stat', 'avg_polar_hr', 'avg_polar_nn50', 'avg_polar_pnn50', 'avg_polar_rmssd', 'avg_polar_rr', 'freq_avg_empatica_gsr', 'max_empatica_bvp', 'max_empatica_bvp_amplitude', 'max_polar_pnn50', 'min_empatica_bvp_amplitude', 'min_garmin_nn50', 'min_garmin_rmssd', 'min_garmin_sdnn', 'min_sacc_duration', 'norm_blink_amount', 'norm_fix_amount', 'range_empatica_bvp_amplitude', 'range_empatica_bvp_median_abs_dev', 'range_raw_pupil', 'std_ica_interpolated_stat', 'std_msband_gsr', 'std_polar_nn50', 'std_polar_pnn50', 'std_raw_pupil']
  117. Training a Ridge CV regression model for subj. CL Rating ...
  118. Features: {'Body Posture': 1, 'Eye': 8, 'Heart': 19, 'Skin': 2}
  119. Avg CV Score: -0.77775
  120. -------------
  121.  
  122. Process finished with exit code 0
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