You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Kernel methods may take several order magnitude more time than regressors.
I propose to introduce a time threshold (t) seconds for training algorithms. When the training time of an algorithm surpasses this threshold, the algorithm's training is terminated, and lazypredict goes to the next algorithm.
We may imagine those following implementation details:
All training algorithms are encapsulated in threads to facilitate time management.
API exposes to the user a time threshold parameter (t).
If the training time exceeds 't', the corresponding thread is terminated, and lazypredict goes to the next training loop.
The text was updated successfully, but these errors were encountered:
Kernel methods may take several order magnitude more time than regressors.
I propose to introduce a time threshold (t) seconds for training algorithms. When the training time of an algorithm surpasses this threshold, the algorithm's training is terminated, and lazypredict goes to the next algorithm.
We may imagine those following implementation details:
The text was updated successfully, but these errors were encountered: