The Netflix Dataset Model Application was evaluated using **Linear Regression** and **Lasso Regression**.
## **Evaluation Metrics**
1.**Loss Functions**:
- R² (Coefficient of Determination) → Score Function
2.**Cross-Validation Score**:
- See [Scikit-learn: Cross Validation](https://scikit-learn.org/stable/modules/cross_validation.html)
## **Comparison Results**
The return values of **R² Score** and **Cross-Validation Score** were analyzed for both models:
-**Linear Regression** generally performed better in terms of both metrics.
-**Lasso Regression**, while effective, showed slightly lower performance due to its regularization, which reduces overfitting but may compromise predictive accuracy for this dataset.
## **Conclusion**
Based on the evaluation, **Linear Regression** is the better model for predicting the release year of Netflix titles using the dataset, as it consistently outperforms Lasso Regression in terms of R² Score and Cross-Validation Score.
