OR If we can significantly boost the training speed, it doesn't matt

[High] Current detox_bot uses MultinomialNB that allows out-of-core training ( means you can keep training it without starting over ) through partial_fit(). However, entire feature is already decided at the first then when training. I see there is a few way, including using word2vec on Keras or etc, and wondering if we can use it. about detox_bot2 HOT 1 CLOSED

freesoft commented on May 28, 2024

[High] Current detox_bot uses MultinomialNB that allows out-of-core training ( means you can keep training it without starting over ) through partial_fit(). However, entire feature is already decided at the first then when training. I see there is a few way, including using word2vec on Keras or etc, and wondering if we can use it.

from detox_bot2.

Comments (1)

freesoft commented on May 28, 2024

yeah either way should work. Is it already implemented in your apache spark PR?

from detox_bot2.

Related Issues (10)

[High] Research if we can use Spark( + MLlib) and replace current scikit-learn based toxic chat classifier. Where to run it(AWS, GCP, etc?) HOT 5
Decide what progress we are going to make and address it to individual member(s) HOT 2
Summarize what progress we made HOT 1
[Low] Update TwitchBot (written in python) and make it runnable and deployable to multiple channel easily. HOT 1
[Low] Adding more stop words. detox_bot uses stopwords which is pre-defined set of words plus a few custom words that I added. However, there are more lot of stopword that's recurring too much or pretty much useless when detecting toxic chat. I would like to decent amount of stop words in there ( not just a, the, this, that, etc ) so that we can expect better accuracy. HOT 2
[HIigh] Writing final report and submit
Research Kubernetes services for detox application HOT 3
write the project proposal HOT 2
submit the project proposal

Comments (1)

Related Issues (10)

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