我正在尝试使用高斯 HMM 预测股市。我不知道模型训练后预测步骤是如何完成的。我不明白准确预测最可能的状态序列如何有助于预测未来价值。
One of the question asked suggest this method: "Use the Viterbi algorithm with the (partial) sequence to obtain the most likely hidden-state-sequence. Take the emission distribution of the last hidden state in this sequence and predict e.g. the mean of that distribution (which often is Gaussian)."
I did not get what he says after predicting most likely state sequence.
I have trained my model using functions available with hmmlearn in python. I have also applied Viterbi algorithm …