Function train

tf_classify_demo/classify.py:28–43

利用无隐藏层的softmax实现简单的分类模型

(samples, sess, x, y, y_, train_step)

saver = tf.train.Saver()

def train(samples, sess, x, y, y_, train_step):
    """
    利用无隐藏层的softmax实现简单的分类模型
    """

    samples.clear_word_vector()
    test_xs, test_ys = samples.test_sets()

    for i in range(10000):
        batch_xs, batch_ys = samples.next_batch(1)
        train_step.run({x: batch_xs, y_: batch_ys})

        correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1))
        accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
        print(accuracy.eval({x: test_xs, y_: test_ys}))
        saver.save(sess, 'data/model/model')

def predict(samples, sess, x, y, y_, train_step):
    x_s = samples.generate_xs('数据科学入门')