标签：mat 数据 from ssi one join filename 方案 nbsp
问题描述：执行下面的代码，报错valueError: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 0
原因：数据量太少
解决方案：增加训练数据量
代码如下：
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() # 建立随机逻辑回归模型，筛选变量
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()]))
标签：mat 数据 from ssi one join filename 方案 nbsp
原文地址：https://www.cnblogs.com/heiao10duan/p/8745810.html
