Created
October 18, 2017 23:35
-
-
Save hide-tono/a5518b29de5bee6109fe8879e188cae8 to your computer and use it in GitHub Desktop.
ADALINE実行結果
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import pandas as pd | |
df = pd.read_csv('https://archive.ics.uci.edu/ml/' | |
'machine-learning-databases/iris/iris.data', header=None) | |
import matplotlib.pyplot as plt | |
import numpy as np | |
y = df.iloc[0:100, 4].values | |
y = np.where(y == 'Iris-setosa', -1, 1) | |
X = df.iloc[0:100, [0, 2]].values | |
fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(8, 4)) | |
ada1 = AdalineGD(n_iter=10, eta=0.01).fit(X, y) | |
ax[0].plot(range(1, len(ada1.cost_) + 1), np.log10(ada1.cost_), marker='o') | |
ax[0].set_xlabel('Epochs') | |
ax[0].set_ylabel('log(Sum-squared-error)') | |
ax[0].set_title('Adaline - Learning rate 0.01') | |
ada2 = AdalineGD(n_iter=10, eta=0.0001).fit(X, y) | |
ax[1].plot(range(1, len(ada2.cost_) + 1), ada2.cost_, marker='o') | |
ax[1].set_xlabel('Epochs') | |
ax[1].set_ylabel('Sum-squared-error') | |
ax[1].set_title('Adaline - Learning rate 0.0001') | |
plt.tight_layout() | |
# plt.savefig('./adaline_1.png', dpi=300) | |
plt.show() |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment