英文:
How to fix TypeError: too many positional arguments when using make_pipeline
问题
由于某种原因，我在以下代码中收到了一个TypeError错误。
from sklearn.preprocessing import PolynomialFeaturesfrom sklearn.linear_model import LinearRegressionfrom sklearn.pipeline import make_pipelinefrom sklearn.model_selection import validation_curvedef PolynomialRegression(degree=2, **kwargs):return make_pipeline(PolynomialFeatures(degree), LinearRegression(**kwargs))train_score, val_score = validation_curve(PolynomialRegression(), X, y,'polynomialfeatures__degree',degree, cv=7)
错误信息如下：
File ~/opt/miniconda3/lib/python3.10/inspect.py:3108, in Signature._bind(self, args, kwargs, partial)3104 else:3105 if param.kind in (_VAR_KEYWORD, _KEYWORD_ONLY):3106 # Looks like we have no parameter for this positional3107 # argument-> 3108 raise TypeError(3109 'too many positional arguments') from None3111 if param.kind == _VAR_POSITIONAL:3112 # We have an '*args'-like argument, let's fill it with3113 # all positional arguments we have left and move on to3114 # the next phase3115 values = [arg_val]TypeError: too many positional arguments
英文:
For some reason I'm getting a TypeError in the following code.
from sklearn.preprocessing import PolynomialFeaturesfrom sklearn.linear_model import LinearRegressionfrom sklearn.pipeline import make_pipelinefrom sklearn.model_selection import validation_curvedef PolynomialRegression(degree=2, **kwargs):return make_pipeline(PolynomialFeatures(degree), LinearRegression(**kwargs))train_score, val_score = validation_curve(PolynomialRegression(), X, y,'polynomialfeatures__degree',degree, cv=7)
> File ~/opt/miniconda3/lib/python3.10/inspect.py:3108, in Signature._bind(self, args, kwargs, partial)
3104 else:
3105 if param.kind in (_VAR_KEYWORD, _KEYWORD_ONLY):
3106 # Looks like we have no parameter for this positional
3107 # argument
-> 3108 raise TypeError(
3109 'too many positional arguments') from None
3111 if param.kind == _VAR_POSITIONAL:
3112 # We have an '*args'-like argument, let's fill it with
3113 # all positional arguments we have left and move on to
3114 # the next phase
3115 values = [arg_val]
TypeError: too many positional arguments
答案1
得分: 0
你分享的代码似乎有一个小错误。在validation_curve函数中，degree参数应该作为一个范围或数值数组传递，而不是一个单一的数值。
from sklearn.preprocessing import PolynomialFeaturesfrom sklearn.linear_model import LinearRegressionfrom sklearn.pipeline import make_pipelinefrom sklearn.model_selection import validation_curvedef PolynomialRegression(degree=2, **kwargs):return make_pipeline(PolynomialFeatures(degree), LinearRegression(**kwargs))degrees = [1, 2, 3, 4, 5] # 用于验证曲线的示例度数train_score, val_score = validation_curve(PolynomialRegression(), X, y,param_name='polynomialfeatures__degree',param_range=degrees,cv=7)
英文:
The code you shared seems to have a small error. The degree parameter in the validation_curve function should be passed as a range or array of values, not as a single value.
from sklearn.preprocessing import PolynomialFeaturesfrom sklearn.linear_model import LinearRegressionfrom sklearn.pipeline import make_pipelinefrom sklearn.model_selection import validation_curvedef PolynomialRegression(degree=2, **kwargs):return make_pipeline(PolynomialFeatures(degree), LinearRegression(**kwargs))degrees = [1, 2, 3, 4, 5] # Example degrees for the validation curvetrain_score, val_score = validation_curve(PolynomialRegression(), X, y,param_name='polynomialfeatures__degree',param_range=degrees,cv=7)
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