hmmlearn ライブラリを使用して特定のデータから最適なシーケンスを予測しようとしていますが、エラーが発生します。私のコードは次のとおりです。
from hmmlearn import hmm
trans_mat = np.array([[0.2,0.6,0.2],[0.4,0.0,0.6],[0.1,0.2,0.7]])
emm_mat = np.array([[0.2,0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1],[0.1,0.1,0.1,0.1,0.2,0.1,0.1,0.1,0.1],[0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.2]])
start_prob = np.array([0.3,0.4,0.3])
X = [3,4,5,6,7]
model = GaussianHMM(n_components = 3, n_iter = 1000)
X = np.array(X)
model.startprob_ = start_prob
model.transmat_ = trans_mat
model.emissionprob_ = emm_mat
# Predict the optimal sequence of internal hidden state
x = model.fit([X])
print(model.decode([X]))
しかし、次のようなエラーが表示されます。
Traceback (most recent call last):
File "hmm_loyalty.py", line 55, in <module>
x = model.fit([X])
File "build/bdist.macosx-10.6-x86_64/egg/hmmlearn/base.py", line 421, in fit
File "build/bdist.macosx-10.6-x86_64/egg/hmmlearn/hmm.py", line 183, in _init
File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/sklearn/cluster/k_means_.py", line 785, in fit
X = self._check_fit_data(X)
File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/sklearn/cluster/k_means_.py", line 758, in _check_fit_data
X.shape[0], self.n_clusters))
ValueError: n_samples=1 should be >= n_clusters=3
これが何を意味するのか、それを解決するために何ができるのか、誰にも分かりますか?