Simple Neural Network get 95.83% accuracy with RMSprop optimizer
Simple Neural Network by using RMSprop optimzer with only 5 layers. Here's the coding. from __future__ import print_function import keras from keras.models import Sequential from keras.layers import Dense, Dropout from keras.optimizers import RMSprop from keras.utils import np_utils import os from six.moves import cPickle as pickle batch_size = 128 num_classes = 10 epochs = 20 def load_data(): test_filename = "notMNIST.pickle" if os.path.exists(test_filename): with open(test_filename, 'rb') as f: letter_dataset = pickle.load(f) return (letter_dataset) lt_dt = load_data() train_dataset = lt_dt['train_dataset'] train_labels = lt_dt['train_labels'] valid_dataset = lt_dt['valid_dataset'] valid_labels = lt_dt['valid_labels'] test_dataset = lt_dt['test_dataset'] test_labels = lt_dt['test_labels'] x_train = train_datase...