22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
22-year-old Happy Birthday
Trained, trained, trained, I will record why not. Ooo, ooo to pass personal blog, although the trouble spots, but comfortable.
Then talk about the US group recently made comments crawling and emotional classification
I used two models to do this thing, a Bayesian classification, one is Bert
Bert outperformed Bayesian classifier, Bert sentiment classification the correctness of the 92.8%
accuracy rate of more than 80% Bayesian classifier, critical for sentiment classification is to enhance the accuracy of data preprocessing reviews
Ideas: crawling Comment -> Categories -> Reviews pretreatment -> divided into good and bad comments Comments -> Import Model -> train -> get results
process result:
