Python Feature_Extractor.extractor示例

示例#1

文件： citprov.py 项目： lwheng/codeforscience2012

 def __init__(self):
   self.dist = Utils.dist()
   self.nltk_Tools = Utils.nltk_tools()
   self.pickler = Utils.pickler()
   self.tools = Utils.tools()
   self.weight = Utils.weight()
   self.dataset_tools = Utils.dataset_tools(self.dist, self.nltk_Tools, self.pickler, self.tools)
   self.extractor = Feature_Extractor.extractor(self.dist, self.nltk_Tools, self.pickler, self.tools, self.weight, "authors", "titles")
   # Load model for prediction
   self.model = self.pickler.loadPickle('ModelCFS.pickle')
   self.model_v2 = self.pickler.loadPickle('ModelCFS_v2.pickle')

示例#2

 def __init__(self):
     self.dist = Utils.dist()
     self.nltk_Tools = Utils.nltk_tools()
     self.pickler = Utils.pickler()
     self.tools = Utils.tools()
     self.weight = Utils.weight()
     self.dataset_tools = Utils.dataset_tools(self.dist, self.nltk_Tools,
                                              self.pickler, self.tools)
     self.extractor = Feature_Extractor.extractor(self.dist,
                                                  self.nltk_Tools,
                                                  self.pickler, self.tools,
                                                  self.weight, "authors",
                                                  "titles")
     # Load model for prediction
     self.model = self.pickler.loadPickle('ModelCFS.pickle')
     self.model_v2 = self.pickler.loadPickle('ModelCFS_v2.pickle')

示例#3

文件： DatasetTBA.py 项目： lwheng/fyp

import Feature_Extractor
import Utils
import sys

if __name__ == '__main__':
  nltk_Tools = Utils.nltk_tools()
  tools = Utils.tools()
  weight = Utils.weight()
  dist = Utils.dist()
  pickler = Utils.pickler()
  dataset_tools = Utils.dataset_tools(dist, nltk_Tools, pickler, tools)

  authors = pickler.loadPickle(pickler.pathAuthors)
  titles = pickler.loadPickle(pickler.pathTitles)

  run = Feature_Extractor.extractor(dist, nltk_Tools, pickler, tools, weight, authors, titles)
  raw = pickler.loadPickle(pickler.pathRaw)
  annotations = pickler.loadPickle(pickler.pathAnnotations)
  experiment = dataset_tools.fetchExperiment(raw)

  (forannotation, keys, X, targets) = dataset_tools.prepDataset(run, raw, experiment, annotations)
  pickler.dumpPickle(forannotation, "For_Annotation")
  pickler.dumpPickle(keys, "DatasetTBA_keys")
  pickler.dumpPickle(X, "DatasetTBA")
  pickler.dumpPickle(targets, "Targets")

  #(forannotation, keys, X) = dataset_tools.prepDatasetCFS(run, raw, experiment)
  #pickler.dumpPickle(forannotation, "For_AnnotationCFS")
  #pickler.dumpPickle(keys, "DatasetTBA_keysCFS")
  #pickler.dumpPickle(X, "DatasetTBACFS")

示例#4

import Feature_Extractor
import Utils
import sys

if __name__ == '__main__':
    nltk_Tools = Utils.nltk_tools()
    tools = Utils.tools()
    weight = Utils.weight()
    dist = Utils.dist()
    pickler = Utils.pickler()
    dataset_tools = Utils.dataset_tools(dist, nltk_Tools, pickler, tools)

    authors = pickler.loadPickle(pickler.pathAuthors)
    titles = pickler.loadPickle(pickler.pathTitles)

    run = Feature_Extractor.extractor(dist, nltk_Tools, pickler, tools, weight,
                                      authors, titles)
    raw = pickler.loadPickle(pickler.pathRaw)
    annotations = pickler.loadPickle(pickler.pathAnnotations)
    experiment = dataset_tools.fetchExperiment(raw)

    experiment = experiment[0:200]

    (forannotation, keys, X,
     targets) = dataset_tools.prepDataset(run, raw, experiment, annotations)
    pickler.dumpPickle(forannotation, "For_Annotation")
    pickler.dumpPickle(keys, "DatasetTBA_keys")
    pickler.dumpPickle(X, "DatasetTBA")
    pickler.dumpPickle(targets, "Targets")

    #(forannotation, keys, X) = dataset_tools.prepDatasetCFS(run, raw, experiment)
    #pickler.dumpPickle(forannotation, "For_AnnotationCFS")