Another solution is to use a list as an index:
regr.fit(x_train[:, [0]], x_train[:, 1])
About the reshape: there's reshape method for each instance of ndarray (see
documentation for numpy.ndarray.reshape). It reshapes current vector, and
the order doesn't matter since you have only one column.
On Wed, Feb 11, 2015 at 9:48 PM, Pagliari, Roberto <rpagli...@appcomsci.com>
wrote:
> The problem with slicing is when the index column is not the first one.
> Would there be a way to do it with slicing.
>
>
>
> I’m also not sure about the first method. The inputs of reshape should be
> vector, new shape and order. What does the line below do?
>
>
>
> Thank yuou,
>
>
>
>
>
> *From:* Artem [mailto:barmaley....@gmail.com]
> *Sent:* Wednesday, February 11, 2015 1:39 PM
> *To:* scikit-learn-general@lists.sourceforge.net
> *Subject:* Re: [Scikit-learn-general] regression with one independent
> variable
>
>
>
> fit expects 2-dimensional input, whereas X[:, 0] is one dimensional. You
> can either reshape it manually:
>
>
>
> regr.fit(x_train[:, 0].reshape((x_train.shape[0], 1)), x_train[:, 1])
>
>
>
> or use slices to select continuous range of columns:
>
>
>
> regr.fit(x_train[:, :1], x_train[:, 1])
>
>
>
> What exception tells you is that x_train is of wrong shape. If x_train was
> 2-dimensional, it's shape would have a 2nd element (with index 1).
>
>
>
> On Wed, Feb 11, 2015 at 9:26 PM, Pagliari, Roberto <
> rpagli...@appcomsci.com> wrote:
>
> I’m trying to make a linear regression with one independent variable and
> one or more dependent variables.
>
>
>
> That does not seem to work. Is that a limitation of regression function?
>
>
>
> regr.fit(x_train[:, 0], x_train[:, 1])
>
>
>
> File
> "/usr/local/lib/python2.7/dist-packages/sklearn/linear_model/base.py", line
> 355, in fit
>
> X, y, self.fit_intercept, self.normalize, self.copy_X)
>
> File
> "/usr/local/lib/python2.7/dist-packages/sklearn/linear_model/base.py", line
> 104, in center_data
>
> X_std = np.ones(X.shape[1])
>
> IndexError: tuple index out of range
>
>
>
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leadership blogs to news, videos, case studies, tutorials and more. Take a
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