Fe Transformer Script 📢

# Fit numeric pipeline if self.numeric_features: self.num_imputer_.fit(X[self.numeric_features]) if self.scale: self.scaler_.fit(X[self.numeric_features])

# Fit encoder for categoricals if self.encode and self.categorical_features: self.encoder_ = OneHotEncoder(handle_unknown='ignore', sparse_output=False) self.encoder_.fit(X[self.categorical_features]) FE Transformer Script

# Imputers and scalers self.num_imputer_ = SimpleImputer(strategy='median') self.cat_imputer_ = SimpleImputer(strategy='most_frequent') self.scaler_ = StandardScaler() if self.scale else None # Fit numeric pipeline if self

def transform(self, X): X_transformed = pd.DataFrame(index=X.index) X): X_transformed = pd.DataFrame(index=X.index)