Reconstruct a Linear Regression Model

Requirements Clarification & Assessment

1. Understanding the Task:

   • You are provided with coefficients from a previous linear regression model but lack the original dataset.
   • The goal is to apply these coefficients to a new dataset and assess the model's performance.

2. Understanding the Coefficients:

   • Ensure you have all necessary coefficients, including the intercept term.
   • Confirm the coefficients are correctly mapped to the corresponding features.

3. New Dataset Preparation:

   • Verify that the new dataset contains the same features as the original dataset.
   • Check for any necessary preprocessing steps such as scaling, encoding, or handling missing values that were applied to the original data.

4. Performance Metrics:

   • Determine the metrics that will be used to evaluate the model's performance on the new dataset (e.g., R-squared, MSE, MAE).

5. Model Update Strategy:

   • Decide if you will use the old coefficients directly, adjust them, or retrain the model from scratch based on performance.

6. Feasibility Assessment:

   • Consider if the features and relationships in the new dataset are expected to be similar to the original dataset, which would justify using the old coefficients.