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Create estimation validation loop #136

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merged 20 commits into from
May 6, 2020
Merged

Create estimation validation loop #136

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d8f9b35
WIP: Create cross validation study
Tanmay-Kulkarni101 Apr 30, 2020
b4fd146
edit inputs for estimators
Tanmay-Kulkarni101 Apr 30, 2020
e0a801a
add preamble comment
Tanmay-Kulkarni101 Apr 30, 2020
ea9de4d
remove redundant variables
Tanmay-Kulkarni101 Apr 30, 2020
2b6d68d
rename the preprocess_data to preprocess_data_by_treatment
Tanmay-Kulkarni101 May 1, 2020
3829f80
process test and validation with parallel operations
Tanmay-Kulkarni101 May 4, 2020
d145be1
scalable bucket size
Tanmay-Kulkarni101 May 5, 2020
ea05b2e
handle buckets with few data points
Tanmay-Kulkarni101 May 5, 2020
c2c1f2a
replace new_outcome with outcome
Tanmay-Kulkarni101 May 5, 2020
a29de33
standardize the behavior of estimate_dummy_outcome
Tanmay-Kulkarni101 May 5, 2020
02e93c1
standardize function calls
Tanmay-Kulkarni101 May 5, 2020
6c9b45b
remove redundant code
Tanmay-Kulkarni101 May 5, 2020
b782878
add optimization for no estimator pipelines
Tanmay-Kulkarni101 May 5, 2020
9a97936
add simulation loop
Tanmay-Kulkarni101 May 5, 2020
032e9bf
reformat base code to reduce computations
Tanmay-Kulkarni101 May 6, 2020
fefd40a
replace transformations with transformation_list
Tanmay-Kulkarni101 May 6, 2020
9e58815
add docstring to functions
Tanmay-Kulkarni101 May 6, 2020
788b4ab
remove WIP header
Tanmay-Kulkarni101 May 6, 2020
cf2d6b4
adjust tests for new input format
Tanmay-Kulkarni101 May 6, 2020
5ebe530
add tests for binary treatments
Tanmay-Kulkarni101 May 6, 2020
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remove redundant variables
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@Tanmay-Kulkarni101
Tanmay-Kulkarni101 committed Apr 30, 2020
commit ea9de4dd68e804991f943c4b84ece97168e694cb
3 changes: 1 addition & 2 deletions dowhy/causal_refuters/dummy_outcome_refuter.py
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Expand Up @@ -217,7 +217,7 @@ def data_preprocess(self):
data_chunks.append( ~self._data[ self._data[treatment_variable_name] ])
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# We use string arguments to account for both 32 and 64 bit varaibles
elif 'float' in variable_type.name or
elif 'float' in variable_type.name or\
'int' in variable_type.name:
# action for continuous variables
data_copy = copy.deepcopy( self._data )
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Expand All @@ -227,7 +227,6 @@ def data_preprocess(self):

elif 'categorical' in variable_type.name:
# Action for categorical variables
categories = list( self._data[treatment_variable_name].cat.categories )
groups = data_copy.groupby(treatment_variable_name)
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data_chunks = [groups.get_group(group) for group in groups ]
else:
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