-
-
Notifications
You must be signed in to change notification settings - Fork 25.9k
Add SVC documentation for properties. #5224
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Conversation
Issue #4687. Documented `fit_status_`, `probA_`, and `probB_`.
0 if correctly fitted, 1 otherwise (will raise warning) | ||
|
||
probA_, probB_ : array | ||
probability estimates, empty array for probability=False |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
What are the shapes, and what are the interpretations?
thanks :) |
parameters used to produce probability estimates from decision values, | ||
empty array for probability=False. See the section about scores and | ||
probabilities in the SVM section of the User Guide for details. | ||
|
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Also thought Section 8 of http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf was useful. Should I include in docstring?
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Can you add it as References
to the docstring? Does it also describe the SVR? Can you check that it is also mentioned in the user guide? Thanks.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
It's in the user guide: http://scikit-learn.org/stable/modules/svm.html#implementation-details.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
ok fair enough.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
probA_ and probB_ are not mentioned in the user-guide, right?
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
http://scikit-learn.org/stable/modules/svm.html#scores-probabilities explains Platt scaling, but doesn't explicitly mention probA_
or probB_
.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Exactly.
It would be good to give a short explanation of what they do so the user doesn't have to look it up. They are the scaling and offset learned in the platt scaling, right? It would be good to give a formula of what they mean. Otherwise they are useless. |
@amueller, anything I should change on the last commit? |
fit_status_ : int | ||
0 if correctly fitted, 1 otherwise (will raise warning) | ||
|
||
probA_, probB_ : array, shape = [n_class * (n_class-1) / 2] |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Each should be on its own line. Though you only need the explanation once.
Otherwise it looks greatk.
Sorry for the long turnaround |
finished in #12427 |
Issue #4687.
Documented
fit_status_
,probA_
, andprobB_
.