The development was carried out under the leadership of Professor Mikhail Babenko and was created by order of the southern branch of the Central Bank of the Russian Federation. To run the neural network, scientists collected and labeled large amounts of data: Articles were automatically collected by scripts and then manually classified based on key parameters. This provides the model with balanced data that eliminates bias in the forecasts, the press service noted.
The system has already shown a high accuracy rate of 93% in classifying news data. This indicator shows the effectiveness of using machine learning for economic analysis.
Source: Ferra
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