[DL] - 정확도 측정

 

Layer 구조

 

import tensorflow as tf
from tensorflow import keras
import numpy as np
import matplotlib.pyplot as plt


fashion_minist = keras.datasets.fashion_mnist
(train_images, train_labels), (test_images, test_labels) = fashion_minist.load_data()
class_names = ['T-shirt/top', 'Trouser', 'Pillover', 'Dress', 'Coat', 'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']

train_images = train_images/ 255.0
test_images = test_images/ 255.0
train_images = train_images.reshape([-1, 28, 28, 1])
test_images = test_images.reshape([-1, 28, 28, 1])

model.compile(optimizer="adam", loss = "sparse_categorical_crossentropy",
              metrics=["accuracy"])
              
model.summary()

tracking = model.fit(train_images, train_labels, epochs=5)

(test_loss, test_acc) =model.evaluate(test_images, test_labels, verbose=2)
print("\n테스트 정확도",test_acc)

def plt_show_acc(history):
  plt.plot(history.history["accuracy"])
  plt.title("Model Accuracy")
  plt.ylabel("Accuracy")
  plt.xlabel("Epoch")
  plt.legend(["Train"], loc=0)
plt_show_acc(tracking)