SK学习，Python

Question

我想做一个由运算符XOR确定的回归。我创建了一套训练集：

然后我创建了一个测试集：

我使用此代码：

import numpy as np
from sklearn import metrics
from sklearn.linear_model import LogisticRegression

data_train = np.loadtxt('1.csv', delimiter=';')
data_test = np.loadtxt('2.csv', delimiter=';')
X = data_train[:, 1:]
y = data_train[:, 0].astype(np.int)
model = LogisticRegression()
model.fit(X, y)
expected = y
predicted = model.predict(X)
#print(metrics.classification_report(expected, predicted))
#print(metrics.confusion_matrix(expected, predicted))
print(model.predict_proba(data_test))

但我有这个警告：

UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.
  'precision', 'predicted', average, warn_for)

这个错误：

ValueError: X has 3 features per sample; expecting 2

但我只有2岁。 如果我做错了，告诉:)。我是新来的