(self, X, Y, V)
| 23 | pass |
| 24 | |
| 25 | def fit(self, X, Y, V): |
| 26 | K = len(set(Y)) # number of classes - assume 0..K-1 |
| 27 | N = len(Y) |
| 28 | self.models = [] |
| 29 | self.priors = [] |
| 30 | for k in range(K): |
| 31 | # gather all the training data for this class |
| 32 | thisX = [x for x, y in zip(X, Y) if y == k] |
| 33 | C = len(thisX) |
| 34 | self.priors.append(np.log(C) - np.log(N)) |
| 35 | |
| 36 | hmm = HMM(5) |
| 37 | hmm.fit(thisX, V=V, print_period=1, learning_rate=1e-2, max_iter=80) |
| 38 | self.models.append(hmm) |
| 39 | |
| 40 | def score(self, X, Y): |
| 41 | N = len(Y) |