LassoCV.coef not implemented (I think)
I was writing an example for my students when I came across what I think is an issue. In version 24.1 using the LassoCV, the <object>.coef variable should have a list of my coeficeients (at least according to my understanding of the documents). However, the variable is not populated nad throws an error 'LassoCV' object has no attribute 'coef' I do have a .coef_ variable which I believe is the coefficient for the best fit only. the alphas and alphas_ variables have a similar issue in that alphas returns nothing while alphas_ returns the list of alphas used. I'm not sure if this is an documentation oversight or a real issue but wanted to get clarification. I can get what I need from o ther methods, but wanted to see if this needed to be addressed. Best Regards, Robert Slater
Hi Robert,
I do have a .coef_ variable which I believe is the coefficient for the best fit only.
`coef` never existed. Fitted attributes always end with underscore. We do not store coefficients for all fitted `alphas_`. We provide some information regarding the MSE path for all tried alphas: https://scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_model_...
the alphas and alphas_ variables have a similar issue in that alphas returns nothing while alphas_ returns the list of alphas used.
You probably created a model such as `model = LasssoCV()`. By default, the parameter `alpha=None` thus accessing it will return None. After fitting, `alphas_` will be automatically created as specified in the documentation. It will correspond to the values tried by cross-validation. If instead, you are passing an array to `alphas` then `alphas_` will be the same as `alphas_` after calling `fit`. Cheers, On Sun, 31 Jan 2021 at 20:45, Robert Slater <rdslater@gmail.com> wrote:
I was writing an example for my students when I came across what I think is an issue. In version 24.1 using the LassoCV, the <object>.coef variable should have a list of my coeficeients (at least according to my understanding of the documents). However, the variable is not populated nad throws an error
'LassoCV' object has no attribute 'coef'
I do have a .coef_ variable which I believe is the coefficient for the best fit only.
the alphas and alphas_ variables have a similar issue in that alphas returns nothing while alphas_ returns the list of alphas used.
I'm not sure if this is an documentation oversight or a real issue but wanted to get clarification.
I can get what I need from o ther methods, but wanted to see if this needed to be addressed.
Best Regards,
Robert Slater _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
-- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/
Appreciate the clarification. I definitely think the docs need some polish as coef_ only returns a single fitting of coefficients and not the coefficients along the path as stated in the api guide. I am seeing alpha_ alphas_ coef_ dual_gap_ as fitted variables (plus a few more) which is slightly different than the guide/api docs (all the names are plural in the api guide) I don't know if there is way to contribute an edit to the docs, I'd be more than happy to do it (Sorry I'm very OCD about such things, and I know this is a minor details)., I'd be happy to suggest the edit through proper channels. On Sun, Jan 31, 2021 at 2:02 PM Guillaume Lemaître <g.lemaitre58@gmail.com> wrote:
Hi Robert,
I do have a .coef_ variable which I believe is the coefficient for the best fit only.
`coef` never existed. Fitted attributes always end with underscore. We do not store coefficients for all fitted `alphas_`. We provide some information regarding the MSE path for all tried alphas: https://scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_model_...
the alphas and alphas_ variables have a similar issue in that alphas returns nothing while alphas_ returns the list of alphas used.
You probably created a model such as `model = LasssoCV()`. By default, the parameter `alpha=None` thus accessing it will return None. After fitting, `alphas_` will be automatically created as specified in the documentation. It will correspond to the values tried by cross-validation. If instead, you are passing an array to `alphas` then `alphas_` will be the same as `alphas_` after calling `fit`.
Cheers,
On Sun, 31 Jan 2021 at 20:45, Robert Slater <rdslater@gmail.com> wrote:
I was writing an example for my students when I came across what I think is an issue. In version 24.1 using the LassoCV, the <object>.coef variable should have a list of my coeficeients (at least according to my understanding of the documents). However, the variable is not populated nad throws an error
'LassoCV' object has no attribute 'coef'
I do have a .coef_ variable which I believe is the coefficient for the best fit only.
the alphas and alphas_ variables have a similar issue in that alphas returns nothing while alphas_ returns the list of alphas used.
I'm not sure if this is an documentation oversight or a real issue but wanted to get clarification.
I can get what I need from o ther methods, but wanted to see if this needed to be addressed.
Best Regards,
Robert Slater _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
-- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/ _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
On Sun, 31 Jan 2021 at 21:24, Robert Slater <rdslater@gmail.com> wrote:
Appreciate the clarification. I definitely think the docs need some polish as coef_ only returns a single fitting of coefficients and not the coefficients along the path as stated in the api guide.
I am confused here. LassoCV states: *coef : *ndarray of shape (n_features,) or (n_targets, n_features) Parameter vector (w in the cost function formula). So it seems exactly what it is returning. It does not return the coefficients along the path. Which documentation are you referring to when stating the API guide (if you could provide a link, it would be really helpful)?
I am seeing
alpha_ alphas_ coef_ dual_gap_
as fitted variables (plus a few more) which is slightly different than the guide/api docs (all the names are plural in the api guide)
I don't know if there is way to contribute an edit to the docs, I'd be more than happy to do it (Sorry I'm very OCD about such things, and I know this is a minor details)., I'd be happy to suggest the edit through proper channels.
You can always open a PR in the GitHub scikit-learn repository because the documentation is actually the docstring from the classes and functions. The user guide documentation is located in the /doc folder and the contributing guide will be helpful to start with: https://scikit-learn.org/stable/developers/contributing.html
On Sun, Jan 31, 2021 at 2:02 PM Guillaume Lemaître <g.lemaitre58@gmail.com> wrote:
Hi Robert,
I do have a .coef_ variable which I believe is the coefficient for the best fit only.
`coef` never existed. Fitted attributes always end with underscore. We do not store coefficients for all fitted `alphas_`. We provide some information regarding the MSE path for all tried alphas: https://scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_model_...
the alphas and alphas_ variables have a similar issue in that alphas returns nothing while alphas_ returns the list of alphas used.
You probably created a model such as `model = LasssoCV()`. By default, the parameter `alpha=None` thus accessing it will return None. After fitting, `alphas_` will be automatically created as specified in the documentation. It will correspond to the values tried by cross-validation. If instead, you are passing an array to `alphas` then `alphas_` will be the same as `alphas_` after calling `fit`.
Cheers,
On Sun, 31 Jan 2021 at 20:45, Robert Slater <rdslater@gmail.com> wrote:
I was writing an example for my students when I came across what I think is an issue. In version 24.1 using the LassoCV, the <object>.coef variable should have a list of my coeficeients (at least according to my understanding of the documents). However, the variable is not populated nad throws an error
'LassoCV' object has no attribute 'coef'
I do have a .coef_ variable which I believe is the coefficient for the best fit only.
the alphas and alphas_ variables have a similar issue in that alphas returns nothing while alphas_ returns the list of alphas used.
I'm not sure if this is an documentation oversight or a real issue but wanted to get clarification.
I can get what I need from o ther methods, but wanted to see if this needed to be addressed.
Best Regards,
Robert Slater _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
-- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/ _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
-- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/
On Sun, 31 Jan 2021 at 21:37, Guillaume Lemaître <g.lemaitre58@gmail.com> wrote:
On Sun, 31 Jan 2021 at 21:24, Robert Slater <rdslater@gmail.com> wrote:
Appreciate the clarification. I definitely think the docs need some polish as coef_ only returns a single fitting of coefficients and not the coefficients along the path as stated in the api guide.
I am confused here. LassoCV states:
*coef : *ndarray of shape (n_features,) or (n_targets, n_features)
Ups, `coef_` indeed (I messed up the copy-paste)
Parameter vector (w in the cost function formula). So it seems exactly what it is returning. It does not return the coefficients along the path. Which documentation are you referring to when stating the API guide (if you could provide a link, it would be really helpful)?
I am seeing
alpha_ alphas_ coef_ dual_gap_
as fitted variables (plus a few more) which is slightly different than the guide/api docs (all the names are plural in the api guide)
I don't know if there is way to contribute an edit to the docs, I'd be more than happy to do it (Sorry I'm very OCD about such things, and I know this is a minor details)., I'd be happy to suggest the edit through proper channels.
You can always open a PR in the GitHub scikit-learn repository because the documentation is actually the docstring from the classes and functions. The user guide documentation is located in the /doc folder and the contributing guide will be helpful to start with: https://scikit-learn.org/stable/developers/contributing.html
On Sun, Jan 31, 2021 at 2:02 PM Guillaume Lemaître < g.lemaitre58@gmail.com> wrote:
Hi Robert,
I do have a .coef_ variable which I believe is the coefficient for the best fit only.
`coef` never existed. Fitted attributes always end with underscore. We do not store coefficients for all fitted `alphas_`. We provide some information regarding the MSE path for all tried alphas: https://scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_model_...
the alphas and alphas_ variables have a similar issue in that alphas returns nothing while alphas_ returns the list of alphas used.
You probably created a model such as `model = LasssoCV()`. By default, the parameter `alpha=None` thus accessing it will return None. After fitting, `alphas_` will be automatically created as specified in the documentation. It will correspond to the values tried by cross-validation. If instead, you are passing an array to `alphas` then `alphas_` will be the same as `alphas_` after calling `fit`.
Cheers,
On Sun, 31 Jan 2021 at 20:45, Robert Slater <rdslater@gmail.com> wrote:
I was writing an example for my students when I came across what I think is an issue. In version 24.1 using the LassoCV, the <object>.coef variable should have a list of my coeficeients (at least according to my understanding of the documents). However, the variable is not populated nad throws an error
'LassoCV' object has no attribute 'coef'
I do have a .coef_ variable which I believe is the coefficient for the best fit only.
the alphas and alphas_ variables have a similar issue in that alphas returns nothing while alphas_ returns the list of alphas used.
I'm not sure if this is an documentation oversight or a real issue but wanted to get clarification.
I can get what I need from o ther methods, but wanted to see if this needed to be addressed.
Best Regards,
Robert Slater _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
-- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/ _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
-- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/
-- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/
Ok its on me--I was reading the return objects for path method. My apologies. On Sun, Jan 31, 2021 at 2:38 PM Guillaume Lemaître <g.lemaitre58@gmail.com> wrote:
On Sun, 31 Jan 2021 at 21:24, Robert Slater <rdslater@gmail.com> wrote:
Appreciate the clarification. I definitely think the docs need some polish as coef_ only returns a single fitting of coefficients and not the coefficients along the path as stated in the api guide.
I am confused here. LassoCV states:
*coef : *ndarray of shape (n_features,) or (n_targets, n_features)
Parameter vector (w in the cost function formula). So it seems exactly what it is returning. It does not return the coefficients along the path. Which documentation are you referring to when stating the API guide (if you could provide a link, it would be really helpful)?
I am seeing
alpha_ alphas_ coef_ dual_gap_
as fitted variables (plus a few more) which is slightly different than the guide/api docs (all the names are plural in the api guide)
I don't know if there is way to contribute an edit to the docs, I'd be more than happy to do it (Sorry I'm very OCD about such things, and I know this is a minor details)., I'd be happy to suggest the edit through proper channels.
You can always open a PR in the GitHub scikit-learn repository because the documentation is actually the docstring from the classes and functions. The user guide documentation is located in the /doc folder and the contributing guide will be helpful to start with: https://scikit-learn.org/stable/developers/contributing.html
On Sun, Jan 31, 2021 at 2:02 PM Guillaume Lemaître < g.lemaitre58@gmail.com> wrote:
Hi Robert,
I do have a .coef_ variable which I believe is the coefficient for the best fit only.
`coef` never existed. Fitted attributes always end with underscore. We do not store coefficients for all fitted `alphas_`. We provide some information regarding the MSE path for all tried alphas: https://scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_model_...
the alphas and alphas_ variables have a similar issue in that alphas returns nothing while alphas_ returns the list of alphas used.
You probably created a model such as `model = LasssoCV()`. By default, the parameter `alpha=None` thus accessing it will return None. After fitting, `alphas_` will be automatically created as specified in the documentation. It will correspond to the values tried by cross-validation. If instead, you are passing an array to `alphas` then `alphas_` will be the same as `alphas_` after calling `fit`.
Cheers,
On Sun, 31 Jan 2021 at 20:45, Robert Slater <rdslater@gmail.com> wrote:
I was writing an example for my students when I came across what I think is an issue. In version 24.1 using the LassoCV, the <object>.coef variable should have a list of my coeficeients (at least according to my understanding of the documents). However, the variable is not populated nad throws an error
'LassoCV' object has no attribute 'coef'
I do have a .coef_ variable which I believe is the coefficient for the best fit only.
the alphas and alphas_ variables have a similar issue in that alphas returns nothing while alphas_ returns the list of alphas used.
I'm not sure if this is an documentation oversight or a real issue but wanted to get clarification.
I can get what I need from o ther methods, but wanted to see if this needed to be addressed.
Best Regards,
Robert Slater _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
-- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/ _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
-- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/ _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
participants (2)
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Guillaume Lemaître -
Robert Slater