谁已经成功使用自制软件在Mac OS X(10.8.4)上安装最新的GCC 4.8.1？当它跑到"制作引导程序"时,我总是被困住.
$brew install gcc48
==> Downloading ftp://gcc.gnu.org/pub/gcc/releases/gcc-4.8.1/gcc-4.8.1.tar.bz2
Already downloaded: /Library/Caches/Homebrew/gcc48-4.8.1.tar.bz2
==> ../configure --build=x86_64-apple-darwin12.4.1 --prefix=/usr/local/Cellar/gc
==> make bootstrap
我想使用隐藏马尔可夫模型（解码问题）来预测隐藏状态。数据是分类的。隐藏状态包括饥饿、休息、锻炼和电影。观察范围包括食品、家居、户外和休闲以及艺术和娱乐。我的程序是首先根据观察序列（Baum-Welch 算法）训练 HMM。然后我进行解码（维特比算法）来预测隐藏状态序列。
我的问题是如何将结果（非负整数）映射到相应的类别，例如饥饿或休息。由于训练算法的非确定性，相同数据的每次训练参数都不同。因此，如果我像下面的代码那样进行映射，则每次隐藏状态序列都会不同。
代码如下：
from __future__ import division
import numpy as np
from hmmlearn import hmm
states = ["Hungry", "Rest", "Exercise", "Movie"]
n_states = len(states)
observations = ["Food", "Home", "Outdoor & Recreation", "Arts & Entertainment"]
# The number in this sequence is the index of observation
category_sequence = [1, 0, 1, 2, 1, 3, 1]
Location = np.array([category_sequence]).T
model = hmm.MultinomialHMM(n_components=n_states).fit(Location)
logprob, result = model.decode(Location)
print "Category:", ", ".join(map(lambda x: observations[x], Location.T[0]))
print "Intent:", ", ".join(map(lambda x: states[x], result))