-
-
Notifications
You must be signed in to change notification settings - Fork 4.4k
New issue
Have a question about this project? # for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “#”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? # to your account
Added note about training mode in 'partial_fit' #1382
Added note about training mode in 'partial_fit' #1382
Conversation
@@ -126,6 +126,8 @@ def get_topic_dist(self, bow, minimum_probability=None, minimum_phi_value=None, | |||
def partial_fit(self, X): | |||
""" | |||
Train model over X. | |||
By default, 'online' mode is used for training the LDA model. | |||
Configure `passes` and `update_every` params at init to choose the mode among 'online', 'mini-batch', 'batch' |
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.
Please add explicit values to use
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.
I have updated the mode names and also added explicit values to use for each mode.
@@ -126,6 +126,11 @@ def get_topic_dist(self, bow, minimum_probability=None, minimum_phi_value=None, | |||
def partial_fit(self, X): | |||
""" | |||
Train model over X. | |||
By default, 'online (single-pass)' mode is used for training the LDA model. | |||
Configure `passes` and `update_every` params at init to choose the mode among : |
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.
Please remove spaces before :
everywhere
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. Doing it right away.
This PR adds a note about the mode used for training in the
partial_fit
function in the sklearn wrapper for LDA model.