Moneyballing individual pitches with a Support Vector Machine
9 months ago
- #Support Vector Machines
- #Machine Learning
- #Baseball Analytics
- Introduction to SVM and its application in binary classification.
- Explanation of Hard Margin SVM and the concept of maximizing the margin between classes.
- Mathematical formulation of the hyperplane and optimization problem for SVM.
- Introduction to Soft Margin SVM for non-linearly separable data.
- Implementation of SVM using gradient descent and NumPy.
- Application of SVM to a baseball dataset to analyze pitch characteristics.
- Comparison of LinearSVC and SVC with RBF kernel performance.
- Visualization of pitch movement and location for whiff prediction.
- Conclusion on the insights gained from SVM analysis in baseball.