title: In Keras "ImageDataGenerator", is "validation_split" parameter a kind of K-fold cross validation?
body: <p>I am trying to do K-fold cross validation on Keras model (with ImageDataGenerator and flow_from_directory for training and validation data), I want to know if the argument "validation_split" in "ImageDataGenerator"</p>
  
  <pre><code>    test_datagen = ImageDataGenerator(
      rescale=1. / 255,
      rotation_range = 180,
      width_shift_range = 0.2,
      height_shift_range = 0.2,
      brightness_range = (0.8, 1.2),
      shear_range = 0.2,
      zoom_range = 0.2,
      horizontal_flip = True,
      vertical_flip = True,
      validation_split = 0.1
  
  )
  
  train_datagen = ImageDataGenerator(
      rotation_range = 180,
      width_shift_range = 0.2,
      height_shift_range = 0.2,
      brightness_range = (0.8, 1.2),
      rescale = 1. / 255,
      shear_range = 0.2,
      zoom_range = 0.2,
      horizontal_flip = True,
      vertical_flip = True,
      validation_split = 0.1
  )
  
  train_generator = train_datagen.flow_from_directory(
      train_data_dir,
      target_size = (img_width, img_height),
      batch_size = batch_size,
      class_mode ='binary',
      seed = 42
  )
  
  validation_generator = test_datagen.flow_from_directory(
      validation_data_dir,
      target_size = (img_width, img_height),
      batch_size = batch_size,
      class_mode = 'binary',
      seed = 42
  )
  
  history = model.fit_generator(
      train_generator,
      steps_per_epoch = nb_train_samples // batch_size,
      epochs = epochs,
      validation_data = validation_generator,
      validation_steps = nb_validation_samples // batch_size)
  </code></pre>
  
  <p>Is the "validation_split = 0.1" means that I've already done 10-fold cross validation on my dataset?</p>