————— ——-
cycler 0.10.0
joblib 0.13.2
kiwisolver 1.1.0
matplotlib 3.0.3
numpy 1.17.1
pandas 0.25.1
pip 19.2.3
pyparsing 2.4.2
python-dateutil 2.8.0
pytz 2019.2
scikit-learn 0.21.3
scipy 1.3.1
setuptools 20.10.1
six 1.12.0
from sklearn import svm
xor_data = [
[0,0,0],
[0,1,0],
[1,0,1],
[1,1,0]
]
data = []
label = []
for row in xor_data:
p = row[0]
q = row[1]
r = row[2]
data.append([p,q])
label.append(r)
clf = svm.SVC(gamma="auto")
clf.fit(data, label)
pre = clf.predict(data)
print("予想結果：", pre)
ok = 0; total = 0
for idx, answer in enumerate(label):
p = pre[idx]
if p == answer: ok += 1
total += 1
print("正解率:", ok, "/", total, "=", ok/total)
[vagrant@localhost python]$ python myapp.py
予想結果： [0 0 0 0]
正解率: 3 / 4 = 0.75
OK、取り敢えず環境は整ってきた
