質問編集履歴
2
プログラムの修正
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@@ -13,16 +13,6 @@
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### 該当のソースコード
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```python
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import numpy as np
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import pandas as pd
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from pandas import DataFrame
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from sklearn.model_selection import train_test_split
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from keras.layers.core import Dense, Activation
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from keras.models import Sequential, load_model
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from keras.optimizers import SGD
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import matplotlib.pyplot as plt
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import csv
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data = pd.read_csv('SPSS.csv', sep=",", header=0)
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train_size = 0.7
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@@ -89,38 +79,10 @@
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for i, row in zip(index, l):
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w.writerow([i] + row)
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graph_name = 'epochs:' + 'epochs'
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plot_everytime = True
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def plot_show_close():
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global plot_everytime
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if plot_everytime:
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plt.show()
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plt.close()
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def plot_acc():
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plt.rc('font', family='serif')
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plt.plot(hist_acc_t)
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plt.plot(hist_acc_v)
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plt.title('Accuracy ({})'.format(graph_name))
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plt.xlabel('epoch')
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plt.ylabel('accuracy')
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plt.legend(['acc', 'val_acc'], loc='lower right')
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plt.savefig('G_Acc' + '.png', dpi=300)
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plt.savefig('G_Acc' + '.eps')
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plot_show_close()
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def plot_loss():
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plt.rc('font', family='serif')
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plt.plot(hist_loss_t)
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plt.plot(hist_loss_v)
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plt.title('Loss ({})'.format(graph_name))
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plt.xlabel('epoch')
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plt.ylabel('loss')
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plt.legend(['loss', 'val_loss'], loc='upper right')
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plt.savefig('G_Loss' + '.png', dpi=300)
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plt.savefig('G_Loss' + '.eps')
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plot_show_close()
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plot_acc()
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plot_loss()
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1
プログラムの修正
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acc = hist.history['acc']
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loss = hist.history['loss']
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'''
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plt.rc('font', family='serif')
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fig = plt.figure()
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plt.plot(range(epochs), acc, label='acc', color='black')
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plt.xlabel('epochs')
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plt.show()
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'''
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index = ['acc_t', 'acc_v', 'loss_t', 'loss_v']
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l = [hist_acc_t, hist_acc_v, hist_loss_t, hist_loss_v]
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