利用郵箱監督機器學習訓練過程

程序說明：利用sklearn機器學習庫，調用svm方法訓練/預測數據結果，最後郵箱發送訓練進度和結果
Note: 需要安裝sklearn機器學習庫, matplotlib

# coding: utf-8

# 載入數據
from sklearn import datasets
digits = datasets.load_digits()
result = 0

# 利用svm訓練和預測
from sklearn import svm
clf = svm.SVC(gamma=0.001, C= 100.)
clf.fit(digits.data[:-1], digits.target[:-1])
x_data = digits.data[-1]
x = x_data.reshape(1, -1)
result = clf.predict(x)

# matplot繪圖
import matplotlib.pyplot as plt
plt.figure(1, (3, 3))
plt.imshow(digits.images[-1], cmap = plt.cm.gray_r, interpolation = 'nearest')
plt.show()

# 郵件發送訓練結果
output = "predict result is：" + str(result[0])

if result != 0:
    import smtplib
    from email.mime.text import MIMEText

    mailto_list = ["××××@qq.com"]
    mail_host = "smtp.126.com"  # 設置服務器
    mail_user = "××××"  # 用戶名
    mail_pass = "××××××××"  # 代理登錄密碼
    mail_postfix = "126.com"  # 發件箱的後綴


    def send_mail(to_list, sub):
        me = "hello" + "<" + mail_user + "@" + mail_postfix + ">"
        msg = MIMEText(output, _subtype='plain', _charset='gb2312')
        msg['Subject'] = sub
        msg['From'] = me
        msg['To'] = ";".join(to_list)
        try:
            server = smtplib.SMTP()
            server.connect(mail_host)
            server.login(mail_user, mail_pass)
            server.sendmail(me, to_list, msg.as_string())
            server.close()
            return True
        except Exception:
            return False


    if __name__ == '__main__':

        if send_mail(mailto_list, "SVM訓練"):
            print("發送成功")
        else:
            print("發送失敗")
else:
    print('未發送')