This example uses ML5 model trained on movie reviews. This model scores the sentiment of text with a value between 0 ("negative") and 10 ("positive"). The movie reviews were truncated to a maximum of 200 words and only the 20,000 most common words in the reviews are used.
-
Notifications
You must be signed in to change notification settings - Fork 1
This example uses model trained on movie reviews. This model scores the sentiment of text with a value between 0 ("negative") and 10 ("positive"). The movie reviews were truncated to a maximum of 200 words and only the 20,000 most common words in the reviews are used.
License
laythfadhala/Sentiment-Analysis
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
This example uses model trained on movie reviews. This model scores the sentiment of text with a value between 0 ("negative") and 10 ("positive"). The movie reviews were truncated to a maximum of 200 words and only the 20,000 most common words in the reviews are used.
Topics
Resources
License
Stars
Watchers
Forks
Packages 0
No packages published