Commit d0681715 authored by MessikommerNico's avatar MessikommerNico

Added comments to the ReadMe file

parent 2d56bf86
...@@ -49,10 +49,16 @@ A household with e.g. a PiN score of 6 in the Wash sector would have a PiN index ...@@ -49,10 +49,16 @@ A household with e.g. a PiN score of 6 in the Wash sector would have a PiN index
tbd tbd
## Predictions In order to include the additional data found on the WorldPop Project website, it is necessary to place the .tif files in
```data/external/literacy/```, ```data/external/population/``` and ```data/external/poverty/```.
## Predictions
The folders containing the scripts of the logistic regression and the random forest are located in ```src/```.
Each model has its own script.
The commands required to train/predict a model can be found in the first lines of the corresponding model script.
The input features as well as the training/testing mode can be adjusted in the main function of the scripts.
## Visualisations ## Visualisations
...@@ -244,11 +244,11 @@ def main(): ...@@ -244,11 +244,11 @@ def main():
# feature_list = ['PopulationGroup', 'Status', 'RespondentSex', 'HeadOfHouseholdSex', 'HeadofHouseholdAge', # feature_list = ['PopulationGroup', 'Status', 'RespondentSex', 'HeadOfHouseholdSex', 'HeadofHouseholdAge',
# 'HeadOfHouseholdMaritalStatus', 'TribeOfHousehold', 'NoOfHouseholdMembers', 'HH'] # 'HeadOfHouseholdMaritalStatus', 'TribeOfHousehold', 'NoOfHouseholdMembers', 'HH']
# feature_list = ['PopulationGroup', 'Status', 'RespondentSex', 'HeadOfHouseholdSex', 'HeadofHouseholdAge',
# 'HeadOfHouseholdMaritalStatus', 'TribeOfHousehold', 'NoOfHouseholdMembers']
feature_list = ['PopulationGroup', 'Status', 'RespondentSex', 'HeadOfHouseholdSex', 'HeadofHouseholdAge', feature_list = ['PopulationGroup', 'Status', 'RespondentSex', 'HeadOfHouseholdSex', 'HeadofHouseholdAge',
'HeadOfHouseholdMaritalStatus', 'TribeOfHousehold', 'NoOfHouseholdMembers', 'poverty', 'population', 'HeadOfHouseholdMaritalStatus', 'TribeOfHousehold', 'NoOfHouseholdMembers']
'literacy'] # feature_list = ['PopulationGroup', 'Status', 'RespondentSex', 'HeadOfHouseholdSex', 'HeadofHouseholdAge',
# 'HeadOfHouseholdMaritalStatus', 'TribeOfHousehold', 'NoOfHouseholdMembers', 'poverty', 'population',
# 'literacy']
target_prediction = ['Wash', 'Shelter', 'Food', 'Livelihood', 'Health', 'Nutrition', 'Education', 'Protection'] target_prediction = ['Wash', 'Shelter', 'Food', 'Livelihood', 'Health', 'Nutrition', 'Education', 'Protection']
...@@ -256,7 +256,7 @@ def main(): ...@@ -256,7 +256,7 @@ def main():
'HeadOfHouseholdMaritalStatus', 'TribeOfHousehold'] 'HeadOfHouseholdMaritalStatus', 'TribeOfHousehold']
need_threshold = 4 need_threshold = 4
runMultipleExeriments(feature_list, target_prediction, categorial_list, need_threshold, parameter_tuning=True) runMultipleExeriments(feature_list, target_prediction, categorial_list, need_threshold, parameter_tuning=False)
# runPredictionKFold(feature_list, target_prediction, categorial_list, need_threshold) # runPredictionKFold(feature_list, target_prediction, categorial_list, need_threshold)
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