python-3.x - 如何解决此 ValueError : only 2 non-keyword arguments accepted sklearn python

Question

你好我是 sklearn 的新手，我正在尝试学习它并使用这个模块根据两个特征预测一些数字这是我得到的错误:

ValueError: only 2 non-keyword arguments accepted

这是我的代码:

    from sklearn.linear_model import LinearRegression
    import numpy as np

    trainingData = np.array([[861, 16012018], [860, 12012018], [859, 9012018], [858, 5012018], [857, 2012018], [856, 29122017], [855, 26122017], [854, 22122017], [853, 19122017]])
    trainingScores = np.array([11,18,23,33,34,6],[10,19,21,33,34,1], [14,18,22,23,31,6],[16,22,29,31,33,10],[21,24,27,30,31,6],[1,14,15,20,27,7],[1,9,10,11,15,8],[2,9,27,31,35,1],[7,13,18,22,33,2])

    clf = LinearRegression(fit_intercept=True)
    clf.fit(trainingScores,trainingData)

   predictionData = np.array([862, 19012018 ])
   x=clf.predict(predictionData)
   print(x)

Answer 1

我不确定你想在这里做什么，但是改变这一行:

trainingScores = np.array([11,18,23,33,34,6],[10,19,21,33,34,1], [14,18,22,23,31,6],[16,22,29,31,33,10],[21,24,27,30,31,6],[1,14,15,20,27,7],[1,9,10,11,15,8],[2,9,27,31,35,1],[7,13,18,22,33,2])

为此(注意数据周围的额外方括号):

trainingScores = np.array([[11,18,23,33,34,6],[10,19,21,33,34,1], [14,18,22,23,31,6],[16,22,29,31,33,10],[21,24,27,30,31,6],[1,14,15,20,27,7],[1,9,10,11,15,8],[2,9,27,31,35,1],[7,13,18,22,33,2]])

然后像这样更改 fit() 中参数的顺序:

clf.fit(trainingData,trainingScores)

最后像这样更改预测数据(再次查看额外的方括号):

predictionData = np.array([[862, 19012018]])

之后您的代码将运行。