(Expert in Information Science) Pattern Recognition#machine Learning
- A function for evaluating “class likeness”.
- Example of a discriminant function: P(input | class) (a function that returns the probability of input belonging to a certain class).
- The Nearest Neighbor Method is also one of the discriminant functions (the distance to each point represents the “class likeness”).
- Manual method for finding the discriminant function:
- Fit a probability distribution (such as a standard distribution) to existing data#probability
- The graph of this distribution becomes the discriminant function.
- The goal is to automate this process (machine learning).
- This is the basis of most class classification machine learning methods.
- Simple SVM: Using points on the boundary (support vectors), separate the classes.