| Autor: |
Ramalingam, V. V., Taruun, P., Raj, Sarang |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 3075 Issue 1, p1-4, 4p |
| Abstrakt: |
This paper aims to predict the price of a cryptocurrency by taking into account various factors that impact its value. Initially, the researchers analyze the daily market trends and study the optimal conditions affecting the cryptocurrency's pricing. They collect data on multiple aspects of cryptocurrency pricing and payment networks that are recorded daily. Using this information, they intend to make the most accurate prediction of the cryptocurrency's daily price. To achieve this, we use a semi-supervised machine learning model called the Transformer package for sentimental analysis and store the data in a file. We use the Random Forest Classifier as a baseline training machinelearning model, and the XGBoost Classifier for improved accuracy and precision to predict the target value for the next day. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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