Pushing model and README files to the repo!

README.md

@@ -23,7 +23,7 @@ This is a regression model trained on the Dynamic Pricing Dataset. It was optimi
 
 ## Intended uses & limitations
 
-This model is designed for dynamic pricing optimization. It is not production-ready and has known limitations in real-world applications.
+[More Information Needed]
 
 ## Training Procedure
 
@@ -158,12 +158,47 @@ Below you can find information related to citation.
 [More Information Needed]
 ```
 
-# Evaluation
+# Training Procedure
+
+The model was trained using grid search to optimize hyperparameters.
 
-## Mean Absolute Error (MAE)
+# Hyperparameters
 
-50.3193
+### Hyperparameters:
 
-## R^2 Score
+- alpha: 1
+- copy_X: True
+- fit_intercept: False
+- max_iter: 1000
+- positive: False
+- precompute: False
+- random_state: None
+- selection: cyclic
+- tol: 0.0001
+- warm_start: False
+
+# Evaluation
 
-0.8854
+## Model Coefficients
+
+### Model Coefficients:
+
+| Feature | Coefficient |
+|---------|-------------|
+| Number_of_Riders | -0.1398 |
+| Number_of_Drivers | 0.4665 |
+| Number_of_Past_Rides | -0.0033 |
+| Average_Ratings | -0.0000 |
+| Expected_Ride_Duration | 3.4973 |
+| Location_Category_Suburban | 0.0000 |
+| Location_Category_Urban | -0.0000 |
+| Customer_Loyalty_Status_Regular | 0.0000 |
+| Customer_Loyalty_Status_Silver | 0.0000 |
+| Time_of_Booking_Evening | -2.4212 |
+| Time_of_Booking_Morning | -0.0000 |
+| Time_of_Booking_Night | 0.0000 |
+| Vehicle_Type_Premium | 39.5754 |
+
+## Regression Equation
+
+-0.1398 * Number_of_Riders + 0.4665 * Number_of_Drivers + -0.0033 * Number_of_Past_Rides + 3.4973 * Expected_Ride_Duration + -2.4212 * Time_of_Booking_Evening + 39.5754 * Vehicle_Type_Premium