I am currently using Python's sklearn for machine learning.
You can create a model and make predictions from that model.
So I have a question. If you want to learn this model again, use that model
Is it possible to do additional learning?
Or do I have to use the data I used for my previous study?
This may be a basic question, but I appreciate your cooperation.
Several models of scikit-learn implement a feature called online learning (or incremental learning).
https://scikit-learn.org/0.18/modules/scaling_strategies.html#incremental-learning
With online learning, you can learn more with additional learning data each time.
The following algorithms support online learning in the scikit-learn classification model:
For additional learning, call the partial_fit
method in the same way as calling the fit method.
For machine learning algorithms that do not support online learning, the fit
method will retrain from scratch using one huge training data that adds additional data to the previous training data.
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