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39 lines
746 B
39 lines
746 B
import clean_text
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# import all our functions
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from clean_text import *
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#!pylint cleantext
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import pandas as pd
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from sklearn.feature_extraction.text import CountVectorizer
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training = [
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" I am master of all",
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"I am a absolute learner"
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]
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generalization = [
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"I am absolute learner learner"
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]
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vectorization = CountVectorizer(
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stop_words = "english",
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preprocessor = process.master_clean_text)
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vectorization.fit(training)
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build_vocab = {
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value:key
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for key , value in vectorization.vocabulary_.items()
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}
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vocab = [build_vocab[i] for i in range(len(build_vocab))]
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extracted = pd.DataFrame(
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data = vectorization.transform(generalization).toarray(),
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index=["generalization"],
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columns=vocab
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)
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print(extracted)
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