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Merged
merged 2 commits into from
Mar 14, 2025
Merged

Add data processing #8

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144b93e
update data processor and efficacy metrics
emmanueljordy Mar 11, 2025
7094ecb
Merge pull request #8 from NGO-Algorithm-Audit/main
emmanueljordy Mar 13, 2025
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14 changes: 7 additions & 7 deletions synthpop/metrics/efficacy_metrics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,15 +76,15 @@ def evaluate(self, real_df: pd.DataFrame, synthetic_df: pd.DataFrame) -> dict:
y_real = real_df[self.target_column]

# Handle categorical encoding only if it's a classification task
if self.task == 'classification':
categorical_cols = X_syn.select_dtypes(include=['object', 'category']).columns.tolist()

categorical_cols = X_syn.select_dtypes(include=['object', 'category']).columns.tolist()

if categorical_cols:
X_syn = pd.get_dummies(X_syn, columns=categorical_cols, drop_first=True)
X_real = pd.get_dummies(X_real, columns=categorical_cols, drop_first=True)
if categorical_cols:
X_syn = pd.get_dummies(X_syn, columns=categorical_cols, drop_first=True)
X_real = pd.get_dummies(X_real, columns=categorical_cols, drop_first=True)

# Align columns in case of different categorical levels between real and synthetic data
X_syn, X_real = X_syn.align(X_real, join='left', axis=1, fill_value=0)
# Align columns in case of different categorical levels between real and synthetic data
X_syn, X_real = X_syn.align(X_real, join='left', axis=1, fill_value=0)

# Model Training and Evaluation
if self.task == 'regression':
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2 changes: 1 addition & 1 deletion synthpop/processor/data_processor.py
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Expand Up @@ -61,7 +61,7 @@ def _preprocess(self, data: pd.DataFrame) -> pd.DataFrame:
data = pd.concat([data, transformed_data], axis=1)

elif dtype == "numerical":
scaler = StandardScaler()
scaler = StandardScaler(with_mean= False, with_std= False)
data[col] = scaler.fit_transform(data[[col]])
self.scalers[col] = scaler

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