Beispiel #1
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def posClassify(classes,wts,voco,testLine):
    global preds
    predict = []
    testList = testLine.split()
    # testList = formatPOSTestInput(testLine)
    # for createdLine in testList:
    for windx in range(len(testList)):
        createdLine = formatPosTestInputNew(windx,testList)
        preds = pc.classify(classes,wts,voco,createdLine)
        predict.append(preds)
    
    return predict
Beispiel #2
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def classify_word(cur, prev, next, g_hash):
    context_string = 'CUR:' + cur + ' PREV:' + prev + ' NEXT:' + next
    clazz = percepclassify.classify(context_string, g_hash)
    return clazz
Beispiel #3
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def	classify(question):
		question = preprocess(question)
		print('classifying')
		coarse_class = percepclassify.classify(question, percepclassify.get_g_hash_from_file(home+'data/models/coarse.model'))
		fine_class = percepclassify.classify(question, percepclassify.get_g_hash_from_file(home+'data/models/fine.'+coarse_class+'.model'))
		return coarse_class+':'+fine_class
def	classify_word(cur, prev, next, g_hash):
		context_string = 'CUR:' + cur + ' PREV:' + prev + ' NEXT:' + next
		clazz = percepclassify.classify(context_string, g_hash)
		return clazz
Beispiel #5
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def make_prediction(vdict, weights, words):
    windex = [vdict[word] if word in vdict else -1 for word in words]
    pred = percepclassify.classify(weights, windex)
    return words[1][5:], pred #strip the "curr:" off of the beginning
Beispiel #6
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def make_prediction(vdict, weights, words):
    windex = [vdict[word] if word in vdict else -1 for word in words]
    pred = percepclassify.classify(weights, windex)
    return words[1][5:], pred  #strip the "curr:" off of the beginning
Beispiel #7
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#!/usr/bin/python3 -tt

import percepclassify

question = input()
coarse_class = percepclassify.classify(question, percepclassify.get_g_hash_from_file('../data/models/coarse.model'))
fine_class = percepclassify.classify(question, percepclassify.get_g_hash_from_file('../data/models/fine.'+coarse_class+'.model'))
print(coarse_class+':'+fine_class)