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22 lines
1.0 KiB
22 lines
1.0 KiB
Features in Wellness:
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Pain [0, 1] - no NaNs
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Illness [0, 0.5, 1] - no NaNs
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Menstruation [0, 1] - 16 NaNs, filled with 0. Not a big statistical difference, so this is fine
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Nutrition [0, 0.5, 1] - 837 NaN, filled with 0. Not a useful feature
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NutritionAdj [0, 1] - 745 NaN, filled with 0. Again not useful
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USGMeasurement [0, 1] 168 NaN, filled with 0.
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USG [1.0...] 4382 NaN, not a useful feature
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TrainingReadiness [0..1] - no NaNs
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Useful features include Pain, Illness, Menstruation, TrainingReadiness
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The others either have too many NaNs present to extract any useful meaning or are just unhelpful features
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to begin with, like Nutrition.
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Notnormalized_with_0NaN_wellness.csv:
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- The only feature of significance that had NaN values put into it were Menstruation, as only 16 NaNs were present
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and wouldn't present any statistical difference either way.
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- Working in the notnormalized_with_0NaN_wellness csv should be functional, just have to remove any string columns
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before putting into algorithms as they are not removed in this version
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