Measure model fit for polynomial












0















I am working on Boston Housing Price dataset. I am trying to determine the model fit (coefficient of determination) of a polynomial model.



X = boston_data["lstat"].values.reshape(-1, 1)

y = boston_data["medv"].values.reshape(-1, 1)



# Transform X into polynomial matrix

poly_2_x = PolynomialFeatures(degree=2).fit_transform(X)



# Fit data to model

poly_2_reg = LinearRegression().fit(poly_2_x, y)



# Calculate coefficient

poly_2_coff = poly_2_reg.score(poly_2_x, y)


However, I am stuck with the following error:
ValueError: Found input variables with inconsistent numbers of samples: [333, 6]



Is there a better way of doing this? Or what should I change to rectify the error?



Thanks!






python coefficients







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    0















    I am working on Boston Housing Price dataset. I am trying to determine the model fit (coefficient of determination) of a polynomial model.



    X = boston_data["lstat"].values.reshape(-1, 1)
    
y = boston_data["medv"].values.reshape(-1, 1)
    

    
# Transform X into polynomial matrix
    
poly_2_x = PolynomialFeatures(degree=2).fit_transform(X)
    

    
# Fit data to model
    
poly_2_reg = LinearRegression().fit(poly_2_x, y)
    

    
# Calculate coefficient
    
poly_2_coff = poly_2_reg.score(poly_2_x, y)


    However, I am stuck with the following error:
    ValueError: Found input variables with inconsistent numbers of samples: [333, 6]



    Is there a better way of doing this? Or what should I change to rectify the error?



    Thanks!






    python coefficients







    share|improve this question

























      0












      0








      0








      I am working on Boston Housing Price dataset. I am trying to determine the model fit (coefficient of determination) of a polynomial model.



      X = boston_data["lstat"].values.reshape(-1, 1)
      
y = boston_data["medv"].values.reshape(-1, 1)
      

      
# Transform X into polynomial matrix
      
poly_2_x = PolynomialFeatures(degree=2).fit_transform(X)
      

      
# Fit data to model
      
poly_2_reg = LinearRegression().fit(poly_2_x, y)
      

      
# Calculate coefficient
      
poly_2_coff = poly_2_reg.score(poly_2_x, y)


      However, I am stuck with the following error:
      ValueError: Found input variables with inconsistent numbers of samples: [333, 6]



      Is there a better way of doing this? Or what should I change to rectify the error?



      Thanks!






      python coefficients







      share|improve this question














      I am working on Boston Housing Price dataset. I am trying to determine the model fit (coefficient of determination) of a polynomial model.



      X = boston_data["lstat"].values.reshape(-1, 1)
      
y = boston_data["medv"].values.reshape(-1, 1)
      

      
# Transform X into polynomial matrix
      
poly_2_x = PolynomialFeatures(degree=2).fit_transform(X)
      

      
# Fit data to model
      
poly_2_reg = LinearRegression().fit(poly_2_x, y)
      

      
# Calculate coefficient
      
poly_2_coff = poly_2_reg.score(poly_2_x, y)


      However, I am stuck with the following error:
      ValueError: Found input variables with inconsistent numbers of samples: [333, 6]



      Is there a better way of doing this? Or what should I change to rectify the error?



      Thanks!






      python coefficients




      python coefficients






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      asked Nov 25 '18 at 6:37









      lodepaslodepas

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