問題描述：執行下面的代碼，報錯valueError: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
原因：數據量太少
解決方案：增加訓練數據量
代碼如下：
filename = "test.csv"
data = pd.read_csv(filename,sep=' ')
data = pd.DataFrame(data)
x = data.iloc[:,:8].as_matrix()
y = data.iloc[:,8].as_matrix()
from sklearn.linear_model import LogisticRegression as LR
from sklearn.linear_model import RandomizedLogisticRegression as RLR
rlr = RLR() # 建立隨機邏輯回歸模型，篩選變量
rlr.fit(x, y)
rlr.get_support()
print (rlr.get_support())
print ("*********************88")
print (u'有效特征：%s' % ','.join(data.columns[rlr.get_support()]))