Exemplos de ModelTrainer._evaluate_sentence_for_text_classification em Python

Exemplo n.º 1

Arquivo: test_utils.py Projeto: UKPLab/emnlp2019-NeuralWeb

def test_multiclass_metrics():

    metric = Metric('Test')
    available_labels = ['A', 'B', 'C']

    predictions = ['A', 'B']
    true_values = ['A']
    ModelTrainer._evaluate_sentence_for_text_classification(
        metric, available_labels, predictions, true_values)

    predictions = ['C', 'B']
    true_values = ['A', 'B']
    ModelTrainer._evaluate_sentence_for_text_classification(
        metric, available_labels, predictions, true_values)

    print(metric)

Exemplo n.º 2

Arquivo: test_utils.py Projeto: bluesea0/ditk

def test_multiclass_metrics():

    metric = Metric("Test")
    available_labels = ["A", "B", "C"]

    predictions = ["A", "B"]
    true_values = ["A"]
    ModelTrainer._evaluate_sentence_for_text_classification(
        metric, available_labels, predictions, true_values
    )

    predictions = ["C", "B"]
    true_values = ["A", "B"]
    ModelTrainer._evaluate_sentence_for_text_classification(
        metric, available_labels, predictions, true_values
    )

    print(metric)