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Runtime error
Runtime error
strengths | |
- the model is trained with almost 15.000 comments and the distribution of the rates are balanced | |
- it can predict the rating more accurate if the actual rating is in between 2 and 4 | |
- capital letters does not affect the output rating | |
weaknesses | |
- the model is having trouble with predicting if the given rating is not consistent with comment itself in terms of sentiment | |
- longer comments tends to be considered as average rating since it increases the neutral score | |
- typo in the comment is affecting the result | |
- exclamation mark and emojis are also affects the output rating | |