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FYI: #10 aims to implement something similar to partial_fit, but with a very different API. What should partial_fit method do exactly? Should it learn on partial data or should it do a "warm start", or both?
partial_fit is a method that some scikit-learn estimators have (traditionally SGDClassifier and MiniBatchKMeans, since 0.14 also Naive Bayes). They allow incremental learning: after each partial_fit, you have a functioning estimator/model, which the next partial fit will adjust. (Similar to warm starts.)
hello,can i ask u one question that how to speed up the learning and predicting precess...
or can you recommend a production version of supervised hmm sequence learning model~ like mahout's hmm~~~~ thanks a lot!!!
I consider this a point or matter of discussion, debate, or dispute: the implementation of a partial_fit method for incremental learning.
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