https://www.selleckchem.com/products/stf-31.html
The linguistic and sentiment features are extracted for further processing. Finally, several state-of-the-art machine learning algorithms are trained to classify the COVID-19-related dataset. These algorithms are then evaluated using various metrics. The results show that the random forest classifier outperforms the other classifiers with an accuracy of 88.50%.The study investigates the influence of the COVID-19 on the rate of RD investment and foreign exchange development of China's most important emerging industry firms. From 2010
Like
Comment
Share
