https://github.com/howl-anderson/microhmm

一个微型的基于 Python 的 HMM (隐马尔可夫模型) 包 | A micro python package for HMM (Hidden Markov Model)
https://github.com/howl-anderson/microhmm

hmm hmm-viterbi-algorithm python viterbi viterbi-algorithm viterbi-decoder viterbi-hmm

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一个微型的基于 Python 的 HMM (隐马尔可夫模型) 包 | A micro python package for HMM (Hidden Markov Model)

• Host: GitHub
• URL: https://github.com/howl-anderson/microhmm
• Owner: howl-anderson
• License: mit
• Created: 2018-07-02T13:11:27.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-01-15T07:38:33.000Z (almost 5 years ago)
• Last Synced: 2024-11-03T16:51:30.954Z (about 2 months ago)
• Topics: hmm, hmm-viterbi-algorithm, python, viterbi, viterbi-algorithm, viterbi-decoder, viterbi-hmm
• Language: Python
• Homepage:
• Size: 44.9 KB
• Stars: 14
• Watchers: 3
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.en-US.md
  • License: LICENSE.txt

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README

        
[中文版本的 README](README.md)

------------------------------

# MicroHMM

A micro python package for HMM (Hidden Markov Model).

## Python version

Only test by using Python3

## Install

### pip

```bash

pip install MicroHMM

```

### source

```bash

pip install git+https://github.com/howl-anderson/MicroHMM.git

```

## Usage

```python

from MicroHMM.hmm import HMMModel

hmm_model = HMMModel()

# train model line by line

# input format: list of (observation, hidden_state) pair

hmm_model.train_one_line([("我", "人称"), ("是", "动词"), ("中国人", "名词")])

hmm_model.train_one_line([("你", "人称"), ("去", "动词"), ("上海", "名词")])

# predict by line

# input format: list of observation

result = hmm_model.predict(["你", "是", "中国人"])

print(result)

```

Output:

```python

[('你', '人称'), ('是', '动词'), ('中国人', '名词')]

```

## Online demo

[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/howl-anderson/MicroHMM/master?filepath=.notebooks%2Fdemo.ipynb)

## Used by

* [MicroTokenizer: 一个微型中文分词引擎 | A micro tokenizer for Chinese](https://github.com/howl-anderson/MicroTokenizer)

## Reference

[Speech and Language Processing > Hidden Markov Models](https://web.stanford.edu/~jurafsky/slp3/9.pdf)