Esempi in Python per parallelClassifier

Esempio n. 1

def learning():
    lexicon_feat, embed_feat = initFeatureProcessors()
    data = json.loads(request.data)
    # try 'lucky @USERID ! good luck @USERID & see you soon :) @USERID @USERID'
    result = parallelClassifier([data], lexicon_feat, embed_feat)
    emotions = result[0]['emotions']
    return jsonify(emotions)

Esempio n. 2

File: app.py Progetto: i-DAT/emotionannotate

def learning():
    lexicon_feat, embed_feat = initFeatureProcessors()
    data = json.loads(request.data)
    # try 'lucky @USERID ! good luck @USERID & see you soon :) @USERID @USERID'
    result = parallelClassifier([data], lexicon_feat, embed_feat)
    emotions = result[0]['emotions']
    return jsonify(emotions)

Esempio n. 3

File: Classification.py Progetto: i-DAT/emotionannotate

def classify(inputdir, outputdir):
    import datetime
    global lexicon_feat, embed_feat
    print datetime.datetime.now()
    tweets = read_tweets(inputdir)
    results = parallelClassifier(tweets, lexicon_feat, embed_feat)
    print datetime.datetime.now()
    write_results(outputdir, results)

Esempio n. 4

File: Classification.py Progetto: i-DAT/emotionannotate

def classify(inputdir, outputdir):
    import datetime

    global lexicon_feat, embed_feat
    print datetime.datetime.now()
    tweets = read_tweets(inputdir)
    results = parallelClassifier(tweets, lexicon_feat, embed_feat)
    print datetime.datetime.now()
    write_results(outputdir, results)