| URN |
etd-0629124-202856 |
Statistics |
This thesis had been viewed 77 times. Download 11 times.
|
| Author |
Chun Lin |
| Author's Email Address |
No Public. |
| Department |
Institute of Industrial Management |
| Year |
2023 |
Semester |
2 |
| Degree |
Master |
Type of Document |
Master's Thesis |
| Language |
zh-TW.Big5 Chinese |
Page Count |
45 |
| Title |
Using Deep Learning Methods to Explore on the Prediction of American Professional Baseball Games |
| Keyword |
accuracy
model optimization
outcome prediction
deep learning
Major League Baseball games
Major League Baseball games
deep learning
outcome prediction
model optimization
accuracy
|
| Abstract |
Lottery is the dream of many people to make money, and prediction of professional baseball games is also one of the activities that everyone is enthusiastic about. However, like other sports, prediction of professional baseball games has always been a very difficult issue. There are many studies in the literature that use various methods to obtain many interesting results, but these results are difficult to apply to actual event prediction. This study attempts to use the advanced artificial intelligence method-deep learning method to explore the prediction research of American professional baseball games, and obtain the characteristics and results of this type of neural network model. These results can provide researchers who are also engaged in this field. Important reference, deep learning neural networks can indeed improve the accuracy of event predictions. This study takes the historical data of the game between the American Giants and the Dodgers as an example to illustrate how to apply this model for prediction research. |
| Advisor Committee |
Chen,Shin-Guang - advisor
Chang,Ping-Chen - co-chair
Yeh,Cheng-Ta - co-chair
|
| Files |
indicate access worldwide |
| Date of Defense |
2024-06-14 |
Date of Submission |
2024-06-30 |
