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June 19, 2016 07:15
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# coding: utf-8 | |
# http://momijiame.tumblr.com/post/114751531866/python-iris-%E3%83%87%E3%83%BC%E3%82%BF%E3%82%BB%E3%83%83%E3%83%88%E3%82%92%E3%82%B5%E3%83%9D%E3%83%BC%E3%83%88%E3%83%99%E3%82%AF%E3%82%BF%E3%83%BC%E3%83%9E%E3%82%B7%E3%83%B3%E3%81%A7%E5%88%86%E9%A1%9E%E3%81%97%E3%81%A6%E3%81%BF%E3%82%8B | |
# https://github.com/levelfour/machine-learning-2014/wiki/%E7%AC%AC1%E5%9B%9E---iris-classification | |
# In[1]: | |
#get_ipython().magic('matplotlib inline') | |
# In[2]: | |
from sklearn.svm import LinearSVC | |
import numpy as np | |
# In[62]: | |
data = [[1,2], [1,4], [2,4], [2,1], [5,1], [4,2]] # 例題6.1の学習データ | |
#label = ["c1", "c1", "c1", "c2", "c2", "c2"] # 正解ラベル | |
label = ["1", "1", "1", "2", "2", "2"] # 正解ラベル | |
print(data) | |
print(label) | |
# In[87]: | |
data = np.asarray(data, np.float32) | |
#data[3:,1] | |
# In[89]: | |
classifier = LinearSVC() # 線形SVC | |
classifier.fit(data, label) # 学習 | |
# In[90]: | |
result = classifier.predict(data) | |
#result | |
# In[66]: | |
# 意味ないけど | |
from sklearn.metrics import accuracy_score | |
accuracy = accuracy_score(label, result) | |
print(accuracy) | |
# ### グラフにプロットしたい | |
# In[67]: | |
import matplotlib.pyplot as plt | |
# In[68]: | |
#plt.scatter(data[:3,0], data[:3,1], c='red') # クラス1 | |
#plt.scatter(data[3:,0], data[3:,1], c='blue') # クラス2 | |
# In[69]: | |
# データの範囲でメッシュ状に点を取る | |
x_min = data[:, 0].min() - 1 | |
x_max = data[:, 0].max() + 1 | |
y_min = data[:, 1].min() - 1 | |
y_max = data[:, 1].max() + 1 | |
grid_interval = 1.0 | |
xx, yy = np.meshgrid( | |
np.arange(x_min, x_max, grid_interval), | |
np.arange(y_min, y_max, grid_interval) | |
) | |
# In[70]: | |
Z = classifier.predict(np.c_[xx.ravel(), yy.ravel()]) | |
#Z | |
# In[71]: | |
Z.reshape(xx.shape) | |
# In[82]: | |
Z = Z.reshape(xx.shape) | |
plt.figure(figsize=(10,6), dpi=80) | |
plt.contourf(xx, yy, Z, cmap=plt.cm.Paired, alpha=0.2) | |
plt.scatter(data[:3,0], data[:3,1], c='red') # クラス1 | |
plt.scatter(data[3:,0], data[3:,1], c='blue') # クラス2 | |
#plt.figure(figsize=(8,6)) | |
plt.grid() | |
plt.savefig("svm.jpg", dpi=80) | |
plt.show() | |
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