GitHub - philiagbo/MachineLearningToClassifyDepressedPatiences: My final year dissertation project. This project takes motor activity data from a control group and a condition group. The data is filtered, cleaned and transformed for appropriate use to find the "best" classification algorithm to identify depressed patients from non-depressed patients

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My final year dissertation project. This project takes motor activity data from a control group and a condition group. The data is filtered, cleaned and transformed for appropriate use to find the "best" classification algorithm to identify depressed patients from non-depressed patients

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
.ipynb_checkpoints		.ipynb_checkpoints
24 Hours Depression Machine Learning.ipynb		24 Hours Depression Machine Learning.ipynb
Condition Data-frame.ipynb		Condition Data-frame.ipynb
Control Data-frame.ipynb		Control Data-frame.ipynb
One Week Depression ML.ipynb		One Week Depression ML.ipynb
Two Week Depression.ipynb		Two Week Depression.ipynb
condition_1.csv		condition_1.csv
condition_10.csv		condition_10.csv
condition_11.csv		condition_11.csv
condition_12.csv		condition_12.csv
condition_13.csv		condition_13.csv
condition_14.csv		condition_14.csv
condition_15.csv		condition_15.csv
condition_16.csv		condition_16.csv
condition_17.csv		condition_17.csv
condition_18.csv		condition_18.csv
condition_19.csv		condition_19.csv
condition_2.csv		condition_2.csv
condition_20.csv		condition_20.csv
condition_21.csv		condition_21.csv
condition_22.csv		condition_22.csv
condition_23.csv		condition_23.csv
condition_3.csv		condition_3.csv
condition_4.csv		condition_4.csv
condition_5.csv		condition_5.csv
condition_6.csv		condition_6.csv
condition_7.csv		condition_7.csv
condition_8.csv		condition_8.csv
condition_9.csv		condition_9.csv
condition_dataframe.csv		condition_dataframe.csv
condition_one_week_dataframe.csv		condition_one_week_dataframe.csv
condition_wide_dataframe.csv		condition_wide_dataframe.csv
control_1.csv		control_1.csv
control_10.csv		control_10.csv
control_11.csv		control_11.csv
control_12.csv		control_12.csv
control_13.csv		control_13.csv
control_14.csv		control_14.csv
control_15.csv		control_15.csv
control_16.csv		control_16.csv
control_17.csv		control_17.csv
control_18.csv		control_18.csv
control_19.csv		control_19.csv
control_2.csv		control_2.csv
control_20.csv		control_20.csv
control_21.csv		control_21.csv
control_22.csv		control_22.csv
control_23.csv		control_23.csv
control_24.csv		control_24.csv
control_25.csv		control_25.csv
control_26.csv		control_26.csv
control_27.csv		control_27.csv
control_28.csv		control_28.csv
control_29.csv		control_29.csv
control_3.csv		control_3.csv
control_30.csv		control_30.csv
control_31.csv		control_31.csv
control_32.csv		control_32.csv
control_4.csv		control_4.csv
control_5.csv		control_5.csv
control_6.csv		control_6.csv
control_7.csv		control_7.csv
control_8.csv		control_8.csv
control_9.csv		control_9.csv
control_dataframe.csv		control_dataframe.csv
control_one_week_dataframe.csv		control_one_week_dataframe.csv
control_wide_dataframe.csv		control_wide_dataframe.csv
first_day_condition.csv		first_day_condition.csv
first_day_control.csv		first_day_control.csv
one_week_condition_features.csv		one_week_condition_features.csv
one_week_control_features.csv		one_week_control_features.csv
scores.csv		scores.csv
two_week_condition.csv		two_week_condition.csv
two_week_control_data.csv		two_week_control_data.csv