Hhj

### Slide: Recursive Feature Selection in Random Forest

**Title:** Recursive Feature Selection Technique

**Overview:**

- Recursive Feature Selection (RFS) is used to improve model accuracy by selecting the most relevant features.

**Key Concepts:**

1. **Feature Importance:**

   - RFS ranks features based on their importance to the model's predictions.

   - Helps in identifying and retaining the most impactful features.

2. **Iterative Process:**

   - Features are recursively removed, and the model is re-evaluated to determine the optimal subset of features.

   - This process continues until the best performing set of features is found.

3. **Model Simplification:**

   - By eliminating irrelevant or less important features, RFS simplifies the model.

   - Reduces overfitting and improves model generalizability.

**Impact on Backtest Performance:**

- **Before RFS:**

  - Absolute Average Prediction Error: 1.51 bp

- **After RFS:**

  - Absolute Average Prediction Error: 1.19 bp

  - This improvement demonstrates the effectiveness of RFS in enhancing model accuracy by focusing on the most relevant features.

**Advantages:**

- **Improved Accuracy:** By selecting the most important features, the model's prediction accuracy improves.

- **Reduced Complexity:** Simplifies the model by removing unnecessary features.

- **Enhanced Generalization:** Leads to better performance on unseen data.

**Visual Aid:**

- (Include a flowchart or diagram illustrating the recursive feature selection process, showing feature ranking, iterative removal, and model re-evaluation.)

---

**Visual Elements:**

- **Title:** "Recursive Feature Selection Technique"

- **Overview:** Brief explanation of RFS and its purpose.

- **Key Concepts:** Bullet points on feature importance, the iterative process, and model simplification.

- **Impact on Backtest Performance:** Highlight the improvement in absolute average prediction error.

- **Advantages:** Bullet points on the benefits of RFS.

- **Visual Aid:** Diagram illustrating the RFS process.

Would you like any additional details or specific formatting for this slide?

Math Encrypt