Multinominal Logistic Regression, Softmax
코드: import tensorflow as tf import numpy as np x_raw = [[1, 2, 1, 1], [2, 1, 3, 2], [3, 1, 3, 4], [4, 1, 5, 5], [1, 7, 5, 5], [1, 2, 5, 6], [1, 6, 6, 6], [1, 7, 7, 7]] y_raw = [[0, 0, 1], [0, 0, 1], [0, 0, 1], [0, 1, 0], [0, 1, 0], [0, 1, 0], [1, 0, 0], [1, 0, 0]] x_data = np.array(x_raw, dtype=np.float32) y_data = np.array(y_raw, dtype=np.float32) nb_classes = 3 tf.model = tf.keras.Sequential()..