run_sample_type_predictor.py 文件源码

def run_sample_type_prediction(tag_to_val, mapped_terms, real_props):

    # Load the dilled vectorizer and model
    vectorizer_f = pr.resource_filename(__name__, join("predict_sample_type", "sample_type_vectorizor.dill"))
    classifier_f = pr.resource_filename(__name__, join("predict_sample_type", "sample_type_classifier.dill"))
    with open(vectorizer_f, "rb") as f:
        vectorizer = dill.load(f)
    with open(classifier_f, "rb") as f:
        model = dill.load(f)

    # Make sample-type prediction
    feat_v = vectorizer.convert_to_features(
        get_ngrams_from_tag_to_val(tag_to_val),
        mapped_terms)
    predicted, confidence = model.predict(
        feat_v,
        mapped_terms,
        real_props)

    return predicted, confidence