1. Time Series Prediction with Mixture of Experts
A ECE539 Project
By: Jiong Fan

2. Introduction Time Series Prediction can be defined as
y(t+1) = f(y(0), y(1), …, y(t-L))
Times Series Prediction has a lot of applications
There exists a lot of method to perform this perdiciton

3. Implementation
The implementation consists 3 experts and gating network
Each of the expert is a MLP implementation
Experts are chosen from a pool of predefined configurations
The Gating Network is another MLP implementation

4. “Time-Series Prediction Competition”
Testing Methodology
Test file is from the class web page
“Time-Series Prediction Competition”
Data file is then divided into 2 partitions
The last 270 is the testing data
The rest is training and tuning data
AR model is used as base model

5. Results

6. AR Model

7. Experts 1 Result

8. Expert 2 Result

9. Expert 3 Result

10. Mixture of Experts Result

11. Table of Errors AR Expert 1 Expert 2 Expert 3 Mixture of Experts

12. Conclusion
The Mixture of Expert system predicts with more accuracy than any of the model tested