Short Text Classification
This project had been deprecated. Maybe use deep learning.
A Modification of LibShortText and LIBLINEAR.
Uses Wissen Text Analyzer
API Exported by Skitai App Engine
Win32 support (need MSVC)
git clone https://gitlab.com/hansroh/haiku cd haiku python setup.py build install
import haiku model_path = "./golforbed" analyzer = haiku.StandardAnalyzer (max_term = 200, stem_level = 2, make_lower_case = 1) trainset = [ ('Golf', "cloudy cold calm"), ('Golf', "sunny warm"), ('Bed', "rainy hot"), ('Golf', "sunny hot windy"), ('Bed', "windy cloudy cold"), ('Bed', "rainy cloudy cold"), ] # training h = haiku.Haiku (model_path, haiku.CL_L2, analyzer) # pruning by document frequency and scoring by meth (FS_CF means category frequency) h.select (data, mindf = 0, maxdf = 0, top = 0, meth = haiku.FS_CF) # set training options: uni/bigram and feature representation h.train (haiku.BIGRAM, haiku.FT_BIN) h.close () # guessing h = haiku.Haiku (model_path, haiku.CL_L2, analyzer) h.load () print (h.guess ("sunny cold windy")) h.close ()
Exporting API through Skitai App Engine
Place model data into app_root/resources/haikus/golforbed.
import haiku import skitai if __name__ == "__main__": pref = skitai.pref () pref.config.resource_dir = skitai.joinpath ('resources') skitai.mount ("/", haiku, "app", pref) skitai.run (port = 5005)
Go to http://127.0.0.1:5000/haiku/golforbed/guess?q=sunny%20cold%20windy.
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