fin separation front/back

backend/regression_strategy.py

@@ -0,0 +1,18 @@
+from sklearn.linear_model import LinearRegression
+
+def perform_regression(data, data_name, target_name):
+    X = data[data_name]
+    y = data[target_name]
+
+    if not isinstance(y.iloc[0], (int, float)):
+        raise ValueError("The target variable should be numeric (continuous) for regression.")
+
+    model = LinearRegression()
+    model.fit(X, y)
+    
+    return model
+
+def make_prediction(model, feature_names, input_values):
+    prediction = model.predict([input_values])
+
+    return prediction[0]